def test_plot_volume_source_estimates():
"""Test interactive plotting of volume source estimates."""
forward = read_forward_solution(fwd_fname)
sample_src = forward['src']
vertices = [s['vertno'] for s in sample_src]
n_verts = sum(len(v) for v in vertices)
n_time = 2
data = np.random.RandomState(0).rand(n_verts, n_time)
vol_stc = VolSourceEstimate(data, vertices, 1, 1)
for mode in ['glass_brain', 'stat_map']:
with pytest.warns(None): # sometimes get scalars/index warning
fig = vol_stc.plot(sample_src, subject='sample',
subjects_dir=subjects_dir,
mode=mode)
# [ax_time, ax_y, ax_x, ax_z]
for ax_idx in [0, 2, 3, 4]:
_fake_click(fig, fig.axes[ax_idx], (0.3, 0.5))
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('shift+right')
with pytest.raises(ValueError, match='must be one of'):
vol_stc.plot(sample_src, 'sample', subjects_dir, mode='abcd')
vertices.append([])
surface_stc = SourceEstimate(data, vertices, 1, 1)
with pytest.raises(ValueError, match='Only Vol'):
plot_volume_source_estimates(surface_stc, sample_src, 'sample',
subjects_dir)
with pytest.raises(ValueError, match='Negative colormap limits'):
vol_stc.plot(sample_src, 'sample', subjects_dir,
clim=dict(lims=[-1, 2, 3], kind='value'))
def test_stc_mpl():
"""Test plotting source estimates with matplotlib."""
sample_src = read_source_spaces(src_fname)
vertices = [s['vertno'] for s in sample_src]
n_time = 5
n_verts = sum(len(v) for v in vertices)
stc_data = np.ones((n_verts * n_time))
stc_data.shape = (n_verts, n_time)
stc = SourceEstimate(stc_data, vertices, 1, 1, 'sample')
with pytest.warns(RuntimeWarning, match='not included'):
stc.plot(subjects_dir=subjects_dir, time_unit='s', views='ven',
hemi='rh', smoothing_steps=2, subject='sample',
backend='matplotlib', spacing='oct1', initial_time=0.001,
colormap='Reds')
fig = stc.plot(subjects_dir=subjects_dir, time_unit='ms', views='dor',
hemi='lh', smoothing_steps=2, subject='sample',
backend='matplotlib', spacing='ico2', time_viewer=True,
colormap='mne')
time_viewer = fig.time_viewer
_fake_click(time_viewer, time_viewer.axes[0], (0.5, 0.5)) # change t
time_viewer.canvas.key_press_event('ctrl+right')
time_viewer.canvas.key_press_event('left')
pytest.raises(ValueError, stc.plot, subjects_dir=subjects_dir,
hemi='both', subject='sample', backend='matplotlib')
pytest.raises(ValueError, stc.plot, subjects_dir=subjects_dir,
time_unit='ss', subject='sample', backend='matplotlib')
plt.close('all')
def test_plot_evoked():
"""Test plotting of evoked
"""
import matplotlib.pyplot as plt
evoked = _get_epochs().average()
with warnings.catch_warnings(record=True):
fig = evoked.plot(proj=True, hline=[1], exclude=[], window_title='foo')
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded & spatial_colors & zorder
evoked.plot(exclude='bads')
evoked.plot(exclude=evoked.info['bads'], spatial_colors=True, gfp=True,
zorder='std')
# test selective updating of dict keys is working.
evoked.plot(hline=[1], units=dict(mag='femto foo'))
evoked_delayed_ssp = _get_epochs_delayed_ssp().average()
evoked_delayed_ssp.plot(proj='interactive')
evoked_delayed_ssp.apply_proj()
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive')
evoked_delayed_ssp.info['projs'] = []
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive')
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', axes='foo')
plt.close('all')
# test GFP only
evoked.plot(gfp='only')
assert_raises(ValueError, evoked.plot, gfp='foo')
evoked.plot_image(proj=True)
# plot with bad channels excluded
evoked.plot_image(exclude='bads', cmap='interactive')
evoked.plot_image(exclude=evoked.info['bads']) # does the same thing
plt.close('all')
evoked.plot_topo() # should auto-find layout
_butterfly_onselect(0, 200, ['mag', 'grad'], evoked)
plt.close('all')
cov = read_cov(cov_fname)
cov['method'] = 'empirical'
evoked.plot_white(cov)
evoked.plot_white([cov, cov])
# Hack to test plotting of maxfiltered data
evoked_sss = evoked.copy()
evoked_sss.info['proc_history'] = [dict(max_info=None)]
evoked_sss.plot_white(cov)
evoked_sss.plot_white(cov_fname)
plt.close('all')
evoked.plot_sensors() # Test plot_sensors
plt.close('all')
def test_plot_sensors():
"""Test plotting of sensor array."""
import matplotlib.pyplot as plt
raw = _get_raw()
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap')
plt.close('all')
def test_plot_tfr_topo():
"""Test plotting of TFR data."""
import matplotlib.pyplot as plt
epochs = _get_epochs()
n_freqs = 3
nave = 1
data = np.random.RandomState(0).randn(len(epochs.ch_names),
n_freqs, len(epochs.times))
tfr = AverageTFR(epochs.info, data, epochs.times, np.arange(n_freqs), nave)
plt.close('all')
fig = tfr.plot_topo(baseline=(None, 0), mode='ratio',
title='Average power', vmin=0., vmax=14.)
# test opening tfr by clicking
num_figures_before = len(plt.get_fignums())
# could use np.reshape(fig.axes[-1].images[0].get_extent(), (2, 2)).mean(1)
with pytest.warns(None): # on old mpl there is a warning
_fake_click(fig, fig.axes[0], (0.08, 0.65))
assert num_figures_before + 1 == len(plt.get_fignums())
plt.close('all')
tfr.plot([4], baseline=(None, 0), mode='ratio', show=False, title='foo')
pytest.raises(ValueError, tfr.plot, [4], yscale='lin', show=False)
# nonuniform freqs
freqs = np.logspace(*np.log10([3, 10]), num=3)
tfr = AverageTFR(epochs.info, data, epochs.times, freqs, nave)
fig = tfr.plot([4], baseline=(None, 0), mode='mean', vmax=14., show=False)
assert fig.axes[0].get_yaxis().get_scale() == 'log'
# one timesample
tfr = AverageTFR(epochs.info, data[:, :, [0]], epochs.times[[1]],
freqs, nave)
with pytest.warns(None): # matplotlib equal left/right
tfr.plot([4], baseline=None, vmax=14., show=False, yscale='linear')
# one frequency bin, log scale required: as it doesn't make sense
# to plot log scale for one value, we test whether yscale is set to linear
vmin, vmax = 0., 2.
fig, ax = plt.subplots()
tmin, tmax = epochs.times[0], epochs.times[-1]
with pytest.warns(RuntimeWarning, match='not masking'):
_imshow_tfr(ax, 3, tmin, tmax, vmin, vmax, None, tfr=data[:, [0], :],
freq=freqs[[-1]], x_label=None, y_label=None,
colorbar=False, cmap=('RdBu_r', True), yscale='log')
fig = plt.gcf()
assert fig.axes[0].get_yaxis().get_scale() == 'linear'
# ValueError when freq[0] == 0 and yscale == 'log'
these_freqs = freqs[:3].copy()
these_freqs[0] = 0
with pytest.warns(RuntimeWarning, match='not masking'):
pytest.raises(ValueError, _imshow_tfr, ax, 3, tmin, tmax, vmin, vmax,
None, tfr=data[:, :3, :], freq=these_freqs, x_label=None,
y_label=None, colorbar=False, cmap=('RdBu_r', True),
yscale='log')
def test_plot_sensors():
"""Test plotting of sensor array."""
import matplotlib.pyplot as plt
raw = _get_raw()
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap')
assert_raises(TypeError, plot_sensors, raw) # needs to be info
plt.close('all')
def test_plot_topo_image_epochs():
"""Test plotting of epochs image topography."""
import matplotlib.pyplot as plt
title = 'ERF images - MNE sample data'
epochs = _get_epochs()
cmap = mne_analyze_colormap(format='matplotlib')
fig = plot_topo_image_epochs(epochs, sigma=0.5, vmin=-200, vmax=200,
colorbar=True, title=title, cmap=cmap)
_fake_click(fig, fig.axes[2], (0.08, 0.64))
plt.close('all')
def test_plot_topomap_interactive():
"""Test interactive topomap projection plotting."""
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
evoked = read_evokeds(evoked_fname, baseline=(None, 0))[0]
evoked.pick_types(meg='mag')
evoked.info['projs'] = []
assert not evoked.proj
evoked.add_proj(compute_proj_evoked(evoked, n_mag=1))
plt.close('all')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.gca()
kwargs = dict(vmin=-240, vmax=240, times=[0.1], colorbar=False, axes=ax,
res=8, time_unit='s')
evoked.copy().plot_topomap(proj=False, **kwargs)
canvas.draw()
image_noproj = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert len(plt.get_fignums()) == 1
ax.clear()
evoked.copy().plot_topomap(proj=True, **kwargs)
canvas.draw()
image_proj = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert not np.array_equal(image_noproj, image_proj)
assert len(plt.get_fignums()) == 1
ax.clear()
evoked.copy().plot_topomap(proj='interactive', **kwargs)
canvas.draw()
image_interactive = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_noproj, image_interactive)
assert not np.array_equal(image_proj, image_interactive)
assert len(plt.get_fignums()) == 2
proj_fig = plt.figure(plt.get_fignums()[-1])
_fake_click(proj_fig, proj_fig.axes[0], [0.5, 0.5], xform='data')
canvas.draw()
image_interactive_click = np.frombuffer(
canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_proj, image_interactive_click)
assert not np.array_equal(image_noproj, image_interactive_click)
_fake_click(proj_fig, proj_fig.axes[0], [0.5, 0.5], xform='data')
canvas.draw()
image_interactive_click = np.frombuffer(
canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_noproj, image_interactive_click)
assert not np.array_equal(image_proj, image_interactive_click)
def test_plot_instance_components():
"""Test plotting of components as instances of raw and epochs."""
raw = _get_raw()
picks = _get_picks(raw)
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2)
with pytest.warns(RuntimeWarning, match='projection'):
ica.fit(raw, picks=picks)
ica.exclude = [0]
fig = ica.plot_sources(raw, title='Components')
keys = ('home', 'home', 'end', 'down', 'up', 'right', 'left', '-', '+',
'=', 'd', 'd', 'pageup', 'pagedown', 'z', 'z', 's', 's', 'f11',
'b')
for key in keys:
fig.canvas.key_press_event(key)
ax = fig.mne.ax_main
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
epochs = _get_epochs()
fig = ica.plot_sources(epochs, title='Components')
for key in keys:
fig.canvas.key_press_event(key)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
def test_plot_instance_components():
"""Test plotting of components as instances of raw and epochs."""
import matplotlib.pyplot as plt
raw = _get_raw()
picks = _get_picks(raw)
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2,
max_pca_components=3, n_pca_components=3)
with pytest.warns(RuntimeWarning, match='projection'):
ica.fit(raw, picks=picks)
fig = ica.plot_sources(raw, exclude=[0], title='Components')
for key in ['down', 'up', 'right', 'left', 'o', '-', '+', '=', 'pageup',
'pagedown', 'home', 'end', 'f11', 'b']:
fig.canvas.key_press_event(key)
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]],
'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
epochs = _get_epochs()
fig = ica.plot_sources(epochs, exclude=[0], title='Components')
for key in ['down', 'up', 'right', 'left', 'o', '-', '+', '=', 'pageup',
'pagedown', 'home', 'end', 'f11', 'b']:
fig.canvas.key_press_event(key)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
def test_plot_sensors():
"""Test plotting of sensor array."""
import matplotlib.pyplot as plt
raw = _get_raw()
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap')
ax = plt.subplot(111)
raw.plot_sensors(ch_groups='position', axes=ax)
raw.plot_sensors(ch_groups='selection')
raw.plot_sensors(ch_groups=[[0, 1, 2], [3, 4]])
assert_raises(ValueError, raw.plot_sensors, ch_groups='asd')
assert_raises(TypeError, plot_sensors, raw) # needs to be info
plt.close('all')
def test_plot_sensors():
"""Test plotting of sensor array."""
import matplotlib.pyplot as plt
raw = _get_raw()
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap')
ax = plt.subplot(111)
raw.plot_sensors(ch_groups='position', axes=ax)
raw.plot_sensors(ch_groups='selection')
raw.plot_sensors(ch_groups=[[0, 1, 2], [3, 4]])
assert_raises(ValueError, raw.plot_sensors, ch_groups='asd')
assert_raises(TypeError, plot_sensors, raw) # needs to be info
plt.close('all')
def test_plot_evoked():
"""Test evoked.plot."""
import matplotlib.pyplot as plt
evoked = _get_epochs().average()
fig = evoked.plot(proj=True, hline=[1], exclude=[], window_title='foo',
time_unit='s')
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded & spatial_colors & zorder
evoked.plot(exclude='bads', time_unit='s')
# test selective updating of dict keys is working.
evoked.plot(hline=[1], units=dict(mag='femto foo'), time_unit='s')
evoked_delayed_ssp = _get_epochs_delayed_ssp().average()
evoked_delayed_ssp.plot(proj='interactive', time_unit='s')
evoked_delayed_ssp.apply_proj()
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', time_unit='s')
evoked_delayed_ssp.info['projs'] = []
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', time_unit='s')
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', axes='foo', time_unit='s')
plt.close('all')
# test GFP only
evoked.plot(gfp='only', time_unit='s')
pytest.raises(ValueError, evoked.plot, gfp='foo', time_unit='s')
# plot with bad channels excluded, spatial_colors, zorder & pos. layout
evoked.rename_channels({'MEG 0133': 'MEG 0000'})
evoked.plot(exclude=evoked.info['bads'], spatial_colors=True, gfp=True,
zorder='std', time_unit='s')
evoked.plot(exclude=[], spatial_colors=True, zorder='unsorted',
time_unit='s')
pytest.raises(TypeError, evoked.plot, zorder='asdf', time_unit='s')
plt.close('all')
evoked.plot_sensors() # Test plot_sensors
plt.close('all')
evoked.pick_channels(evoked.ch_names[:4])
with catch_logging() as log_file:
evoked.plot(verbose=True, time_unit='s')
assert 'Need more than one' in log_file.getvalue()
def test_remove_annotations(raw, hide_which):
"""Test that right-click doesn't remove hidden annotation spans."""
ann = Annotations(onset=[2, 1],
duration=[1, 3],
description=['foo', 'bar'])
raw.set_annotations(ann)
assert len(raw.annotations) == 2
fig = raw.plot()
fig.canvas.key_press_event('a') # start annotation mode
checkboxes = fig.mne.show_hide_annotation_checkboxes
for which in hide_which:
checkboxes.set_active(which)
_fake_click(fig, fig.mne.ax_main, (2.5, 0.1), xform='data', button=3)
assert len(raw.annotations) == len(hide_which)
def test_plot_epochs_clicks(epochs, epochs_full, capsys, mpl_backend):
"""Test plot_epochs mouse interaction."""
fig = epochs.plot(events=epochs.events)
x = fig.mne.traces[0].get_xdata()[3]
y = fig.mne.traces[0].get_ydata()[3]
n_epochs = len(epochs)
epoch_num = fig.mne.inst.selection[0]
# test (un)marking bad epochs
fig._fake_click([x, y], xform='data') # mark a bad epoch
assert epoch_num in fig.mne.bad_epochs
fig._fake_click([x, y], xform='data') # unmark it
assert epoch_num not in fig.mne.bad_epochs
fig._fake_click([x, y], xform='data') # mark it bad again
assert epoch_num in fig.mne.bad_epochs
# test vline
fig._fake_keypress('escape') # close and drop epochs
fig._close_event() # XXX workaround, MPL Agg doesn't trigger close event
assert (n_epochs - 1 == len(epochs))
# test marking bad channels
# need more than 1 epoch this time
fig = epochs_full.plot(n_epochs=3)
data_ax = fig.mne.ax_main
# ToDo: Tick-Labels will be accessed differently in pyqtgraph.
first_ch = data_ax.get_yticklabels()[0].get_text()
assert first_ch not in fig.mne.info['bads']
_click_ch_name(fig, ch_index=0, button=1) # click ch name to mark bad
assert first_ch in fig.mne.info['bads']
# test clicking scrollbars
_fake_click(fig, fig.mne.ax_vscroll, [0.5, 0.5])
_fake_click(fig, fig.mne.ax_hscroll, [0.5, 0.5])
# test moving bad epoch offscreen
fig._fake_keypress('right') # move right
x = fig.mne.traces[0].get_xdata()[-3]
y = fig.mne.traces[0].get_ydata()[-3]
fig._fake_click([x, y], xform='data') # mark a bad epoch
fig._fake_keypress('left') # move back
out, err = capsys.readouterr()
assert 'out of bounds' not in out
assert 'out of bounds' not in err
fig._fake_keypress('escape')
fig._close_event() # XXX workaround, MPL Agg doesn't trigger close event
assert len(epochs_full) == 6
# test rightclick → image plot
fig = epochs_full.plot()
_click_ch_name(fig, ch_index=0, button=3) # show image plot
assert len(fig.mne.child_figs) == 1
# test scroll wheel
fig._fake_scroll(0.5, 0.5, -0.5) # scroll down
fig._fake_scroll(0.5, 0.5, 0.5) # scroll up
def test_plot_evoked():
"""Test evoked.plot."""
evoked = _get_epochs().average()
fig = evoked.plot(proj=True, hline=[1], exclude=[], window_title='foo',
time_unit='s')
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded & spatial_colors & zorder
evoked.plot(exclude='bads', time_unit='s')
# test selective updating of dict keys is working.
evoked.plot(hline=[1], units=dict(mag='femto foo'), time_unit='s')
evoked_delayed_ssp = _get_epochs_delayed_ssp().average()
evoked_delayed_ssp.plot(proj='interactive', time_unit='s')
evoked_delayed_ssp.apply_proj()
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', time_unit='s')
evoked_delayed_ssp.info['projs'] = []
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', time_unit='s')
pytest.raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', axes='foo', time_unit='s')
plt.close('all')
# test GFP only
evoked.plot(gfp='only', time_unit='s')
pytest.raises(ValueError, evoked.plot, gfp='foo', time_unit='s')
# plot with bad channels excluded, spatial_colors, zorder & pos. layout
evoked.rename_channels({'MEG 0133': 'MEG 0000'})
evoked.plot(exclude=evoked.info['bads'], spatial_colors=True, gfp=True,
zorder='std', time_unit='s')
evoked.plot(exclude=[], spatial_colors=True, zorder='unsorted',
time_unit='s')
pytest.raises(TypeError, evoked.plot, zorder='asdf', time_unit='s')
plt.close('all')
evoked.plot_sensors() # Test plot_sensors
plt.close('all')
evoked.pick_channels(evoked.ch_names[:4])
with catch_logging() as log_file:
evoked.plot(verbose=True, time_unit='s')
assert 'Need more than one' in log_file.getvalue()
def test_stc_mpl():
"""Test plotting source estimates with matplotlib."""
import matplotlib.pyplot as plt
sample_src = read_source_spaces(src_fname)
vertices = [s['vertno'] for s in sample_src]
n_time = 5
n_verts = sum(len(v) for v in vertices)
stc_data = np.ones((n_verts * n_time))
stc_data.shape = (n_verts, n_time)
stc = SourceEstimate(stc_data, vertices, 1, 1, 'sample')
with pytest.warns(RuntimeWarning, match='not included'):
stc.plot(subjects_dir=subjects_dir,
time_unit='s',
views='ven',
hemi='rh',
smoothing_steps=2,
subject='sample',
backend='matplotlib',
spacing='oct1',
initial_time=0.001,
colormap='Reds')
fig = stc.plot(subjects_dir=subjects_dir,
time_unit='ms',
views='dor',
hemi='lh',
smoothing_steps=2,
subject='sample',
backend='matplotlib',
spacing='ico2',
time_viewer=True,
colormap='mne')
time_viewer = fig.time_viewer
_fake_click(time_viewer, time_viewer.axes[0], (0.5, 0.5)) # change t
time_viewer.canvas.key_press_event('ctrl+right')
time_viewer.canvas.key_press_event('left')
pytest.raises(ValueError,
stc.plot,
subjects_dir=subjects_dir,
hemi='both',
subject='sample',
backend='matplotlib')
pytest.raises(ValueError,
stc.plot,
subjects_dir=subjects_dir,
time_unit='ss',
subject='sample',
backend='matplotlib')
plt.close('all')
def test_plot_topomap_interactive():
"""Test interactive topomap projection plotting."""
evoked = read_evokeds(evoked_fname, baseline=(None, 0))[0]
evoked.pick_types(meg='mag')
evoked.info['projs'] = []
assert not evoked.proj
evoked.add_proj(compute_proj_evoked(evoked, n_mag=1))
plt.close('all')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.gca()
kwargs = dict(vmin=-240, vmax=240, times=[0.1], colorbar=False, axes=ax,
res=8, time_unit='s')
evoked.copy().plot_topomap(proj=False, **kwargs)
canvas.draw()
image_noproj = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert len(plt.get_fignums()) == 1
ax.clear()
evoked.copy().plot_topomap(proj=True, **kwargs)
canvas.draw()
image_proj = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert not np.array_equal(image_noproj, image_proj)
assert len(plt.get_fignums()) == 1
ax.clear()
evoked.copy().plot_topomap(proj='interactive', **kwargs)
canvas.draw()
image_interactive = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_noproj, image_interactive)
assert not np.array_equal(image_proj, image_interactive)
assert len(plt.get_fignums()) == 2
proj_fig = plt.figure(plt.get_fignums()[-1])
_fake_click(proj_fig, proj_fig.axes[0], [0.5, 0.5], xform='data')
canvas.draw()
image_interactive_click = np.frombuffer(
canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_proj, image_interactive_click)
assert not np.array_equal(image_noproj, image_interactive_click)
_fake_click(proj_fig, proj_fig.axes[0], [0.5, 0.5], xform='data')
canvas.draw()
image_interactive_click = np.frombuffer(
canvas.tostring_rgb(), dtype='uint8')
assert_array_equal(image_noproj, image_interactive_click)
assert not np.array_equal(image_proj, image_interactive_click)
def test_plot_topo_image_epochs():
"""Test plotting of epochs image topography."""
import matplotlib.pyplot as plt
title = 'ERF images - MNE sample data'
epochs = _get_epochs()
cmap = mne_analyze_colormap(format='matplotlib')
fig = plot_topo_image_epochs(epochs,
sigma=0.5,
vmin=-200,
vmax=200,
colorbar=True,
title=title,
cmap=cmap)
_fake_click(fig, fig.axes[2], (0.08, 0.64))
plt.close('all')
def test_plot_topo_image_epochs():
"""Test plotting of epochs image topography."""
title = 'ERF images - MNE sample data'
epochs = _get_epochs()
epochs.load_data()
cmap = mne_analyze_colormap(format='matplotlib')
data_min = epochs._data.min()
plt.close('all')
fig = plot_topo_image_epochs(epochs, sigma=0.5, vmin=-200, vmax=200,
colorbar=True, title=title, cmap=cmap)
assert epochs._data.min() == data_min
num_figures_before = len(plt.get_fignums())
_fake_click(fig, fig.axes[0], (0.08, 0.64))
assert num_figures_before + 1 == len(plt.get_fignums())
plt.close('all')
def test_plot_ica_sources():
"""Test plotting of ICA panel."""
import matplotlib.pyplot as plt
raw = read_raw_fif(raw_fname).crop(0, 1).load_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
ecg=False,
eog=False,
exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
ica.exclude = [1]
fig = ica.plot_sources(raw)
fig.canvas.key_press_event('escape')
# Sadly close_event isn't called on Agg backend and the test always passes.
assert_array_equal(ica.exclude, [1])
raw.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=epochs)
epochs.info['bads'] = []
with warnings.catch_warnings(record=True): # no labeled objects mpl
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(
fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.plot_sources(evoked, exclude=[0])
ica.exclude = [0]
ica.plot_sources(evoked) # does the same thing
ica.labels_ = dict(eog=[0])
ica.labels_['eog/0/crazy-channel'] = [0]
ica.plot_sources(evoked) # now with labels
assert_raises(ValueError, ica.plot_sources, 'meeow')
plt.close('all')
def test_inspect_annotations(tmp_path):
"""Test inspection of Annotations."""
import matplotlib
import matplotlib.pyplot as plt
matplotlib.use('Agg')
plt.close('all')
bids_root = setup_bids_test_dir(tmp_path)
bids_path = _bids_path.copy().update(root=bids_root)
raw = read_raw_bids(bids_path=bids_path, verbose='error')
orig_annotations = raw.annotations.copy()
inspect_dataset(bids_path, find_flat=False)
raw_fig = mne_bids.inspect._global_vars['raw_fig']
_add_annotation(raw_fig)
# Close window and save changes.
raw_fig.canvas.key_press_event(raw_fig.mne.close_key)
fig_dialog = mne_bids.inspect._global_vars['dialog_fig']
fig_dialog.canvas.key_press_event('return')
# Ensure changes were saved.
raw = read_raw_bids(bids_path=bids_path, verbose='error')
assert 'BAD_test' in raw.annotations.description
annot_idx = raw.annotations.description == 'BAD_test'
assert raw.annotations.duration[annot_idx].squeeze() == 4
# Remove the Annotation.
inspect_dataset(bids_path, find_flat=False)
raw_fig = mne_bids.inspect._global_vars['raw_fig']
data_ax = raw_fig.mne.ax_main
raw_fig.canvas.key_press_event('a') # Toggle Annotation mode
_fake_click(raw_fig,
data_ax, [1., 1.],
xform='data',
button=3,
kind='press')
# Close window and save changes.
raw_fig.canvas.key_press_event(raw_fig.mne.close_key)
fig_dialog = mne_bids.inspect._global_vars['dialog_fig']
fig_dialog.canvas.key_press_event('return')
# Ensure changes were saved.
raw = read_raw_bids(bids_path=bids_path, verbose='error')
assert 'BAD_test' not in raw.annotations.description
assert raw.annotations == orig_annotations
def test_plot_evoked():
"""Test plotting of evoked
"""
import matplotlib.pyplot as plt
evoked = _get_epochs().average()
with warnings.catch_warnings(record=True):
fig = evoked.plot(proj=True, hline=[1], exclude=[])
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
evoked.plot(exclude='bads')
evoked.plot(exclude=evoked.info['bads']) # does the same thing
# test selective updating of dict keys is working.
evoked.plot(hline=[1], units=dict(mag='femto foo'))
evoked_delayed_ssp = _get_epochs_delayed_ssp().average()
evoked_delayed_ssp.plot(proj='interactive')
evoked_delayed_ssp.apply_proj()
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive')
evoked_delayed_ssp.info['projs'] = []
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive')
assert_raises(RuntimeError, evoked_delayed_ssp.plot,
proj='interactive', axes='foo')
evoked.plot_image(proj=True)
# plot with bad channels excluded
evoked.plot_image(exclude='bads')
evoked.plot_image(exclude=evoked.info['bads']) # does the same thing
plt.close('all')
cov = read_cov(cov_fname)
cov['method'] = 'empirical'
evoked.plot_white(cov)
evoked.plot_white([cov, cov])
# Hack to test plotting of maxfiltered data
evoked_sss = evoked.copy()
evoked_sss.info['proc_history'] = [dict(max_info=None)]
evoked_sss.plot_white(cov)
def test_plot_volume_source_estimates(mode, stype, init_t, want_t, init_p,
want_p, bg_img):
"""Test interactive plotting of volume source estimates."""
forward = read_forward_solution(fwd_fname)
sample_src = forward['src']
if init_p is not None:
init_p = np.array(init_p) / 1000.
vertices = [s['vertno'] for s in sample_src]
n_verts = sum(len(v) for v in vertices)
n_time = 2
data = np.random.RandomState(0).rand(n_verts, n_time)
if stype == 'vec':
stc = VolVectorSourceEstimate(np.tile(data[:, np.newaxis], (1, 3, 1)),
vertices, 1, 1)
else:
assert stype == 's'
stc = VolSourceEstimate(data, vertices, 1, 1)
with pytest.warns(None): # sometimes get scalars/index warning
with catch_logging() as log:
fig = stc.plot(sample_src,
subject='sample',
subjects_dir=subjects_dir,
mode=mode,
initial_time=init_t,
initial_pos=init_p,
bg_img=bg_img,
verbose=True)
log = log.getvalue()
want_str = 't = %0.3f s' % want_t
assert want_str in log, (want_str, init_t)
want_str = '(%0.1f, %0.1f, %0.1f) mm' % want_p
assert want_str in log, (want_str, init_p)
for ax_idx in [0, 2, 3, 4]:
_fake_click(fig, fig.axes[ax_idx], (0.3, 0.5))
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('shift+right')
if bg_img is not None:
with pytest.raises(FileNotFoundError, match='MRI file .* not found'):
stc.plot(sample_src,
subject='sample',
subjects_dir=subjects_dir,
mode='stat_map',
bg_img='junk.mgz')
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
import matplotlib.pyplot as plt
res = 8
fast_test = {"res": res, "contours": 0, "sensors": False}
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname),
n_components=2,
max_pca_components=3,
n_pca_components=3)
ica_picks = _get_picks(raw)
with warnings.catch_warnings(record=True):
ica.fit(raw, picks=ica_picks)
warnings.simplefilter('always', UserWarning)
with warnings.catch_warnings(record=True):
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components,
image_interp='bilinear',
colorbar=True,
**fast_test)
# test interactive mode (passing 'inst' arg)
plt.close('all')
ica.plot_components([0, 1], image_interp='bilinear', inst=raw, res=16)
fig = plt.gcf()
ax = [a for a in fig.get_children() if isinstance(a, plt.Axes)]
lbl = ax[1].get_label()
_fake_click(fig, ax[1], (0., 0.), xform='data')
c_fig = plt.gcf()
ax = [a for a in c_fig.get_children() if isinstance(a, plt.Axes)]
labels = [a.get_label() for a in ax]
for l in ['topomap', 'image', 'erp', 'spectrum', 'variance']:
assert_true(l in labels)
topomap_ax = ax[labels.index('topomap')]
title = topomap_ax.get_title()
assert_true(lbl == title)
ica.info = None
assert_raises(ValueError, ica.plot_components, 1)
assert_raises(RuntimeError, ica.plot_components, 1, ch_type='mag')
plt.close('all')
def test_plot_ica_sources():
"""Test plotting of ICA panel
"""
import matplotlib.pyplot as plt
raw = io.read_raw_fif(raw_fname,
preload=False).crop(0, 1, copy=False).load_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info, meg=True, eeg=False, stim=False,
ecg=False, eog=False, exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
ica.exclude = [1]
fig = ica.plot_sources(raw)
fig.canvas.key_press_event('escape')
# Sadly close_event isn't called on Agg backend and the test always passes.
assert_array_equal(ica.exclude, [1])
raw.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=epochs)
epochs.info['bads'] = []
with warnings.catch_warnings(record=True): # no labeled objects mpl
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.plot_sources(evoked, exclude=[0])
ica.exclude = [0]
ica.plot_sources(evoked) # does the same thing
ica.labels_ = dict(eog=[0])
ica.labels_['eog/0/crazy-channel'] = [0]
ica.plot_sources(evoked) # now with labels
assert_raises(ValueError, ica.plot_sources, 'meeow')
plt.close('all')
def test_clickable_image():
"""Test the ClickableImage class."""
# Gen data and create clickable image
im = np.random.randn(100, 100)
clk = ClickableImage(im)
clicks = [(12, 8), (46, 48), (10, 24)]
# Generate clicks
for click in clicks:
_fake_click(clk.fig, clk.ax, click, xform='data')
assert_allclose(np.array(clicks), np.array(clk.coords))
assert_true(len(clicks) == len(clk.coords))
# Exporting to layout
lt = clk.to_layout()
assert_true(lt.pos.shape[0] == len(clicks))
assert_allclose(lt.pos[1, 0] / lt.pos[2, 0],
clicks[1][0] / float(clicks[2][0]))
def test_plot_epochs():
"""Test epoch plotting"""
import matplotlib.pyplot as plt
epochs = _get_epochs()
epochs.plot(scalings=None, title='Epochs', trellis=False)
plt.close('all')
fig = epochs[0].plot(picks=[0, 2, 3], scalings=None, trellis=False)
fig.canvas.key_press_event('escape')
plt.close('all')
fig = epochs.plot(trellis=False)
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('right')
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('end')
fig.canvas.resize_event()
fig.canvas.close_event() # closing and epoch dropping
plt.close('all')
with warnings.catch_warnings(record=True):
fig = epochs.plot(trellis=False)
# 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, 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')
assert_raises(RuntimeError, epochs.plot, picks=[], trellis=False)
plt.close('all')
def test_plot_epochs_keypresses():
"""Test plot_epochs keypress interaction."""
epochs = _get_epochs(stop=15).load_data() # we need more than 1 epoch
epochs.drop_bad(dict(mag=4e-12)) # for histogram plot coverage
fig = epochs.plot(n_epochs=3)
data_ax = fig.mne.ax_main
# make sure green vlines are visible first (for coverage)
sample_idx = len(epochs.times) // 2 # halfway through the first epoch
x = fig.mne.traces[0].get_xdata()[sample_idx]
y = (fig.mne.traces[0].get_ydata()[sample_idx] +
fig.mne.traces[1].get_ydata()[sample_idx]) / 2
_fake_click(fig, data_ax, [x, y], xform='data') # click between traces
# test keys
keys = ('pagedown', 'down', 'up', 'down', 'right', 'left', '-', '+', '=',
'd', 'd', 'pageup', 'home', 'shift+right', 'end', 'shift+left',
'z', 'z', 's', 's', 'f11', '?', 'h', 'j', 'b')
for key in keys * 2: # test twice → once in normal, once in butterfly view
fig.canvas.key_press_event(key)
_fake_click(fig, data_ax, [x, y], xform='data', button=3) # remove vlines
def test_plot_instance_components():
"""Test plotting of components as instances of raw and epochs."""
import matplotlib.pyplot as plt
raw = _get_raw()
picks = _get_picks(raw)
ica = ICA(noise_cov=read_cov(cov_fname),
n_components=2,
max_pca_components=3,
n_pca_components=3)
with warnings.catch_warnings(record=True): # bad proj
ica.fit(raw, picks=picks)
fig = ica.plot_sources(raw, exclude=[0], title='Components')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.key_press_event('right')
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('o')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event('=')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event('pagedown')
fig.canvas.key_press_event('home')
fig.canvas.key_press_event('end')
fig.canvas.key_press_event('f11')
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
epochs = _get_epochs()
fig = ica.plot_sources(epochs, exclude=[0], title='Components')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.key_press_event('right')
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('o')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event('=')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event('pagedown')
fig.canvas.key_press_event('home')
fig.canvas.key_press_event('end')
fig.canvas.key_press_event('f11')
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
def test_plot_ica_sources():
"""Test plotting of ICA panel
"""
import matplotlib.pyplot as plt
raw = io.Raw(raw_fname, preload=False)
raw.crop(0, 1, copy=False)
raw.preload_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
ecg=False,
eog=False,
exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
raw.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=epochs)
epochs.info['bads'] = []
with warnings.catch_warnings(record=True): # no labeled objects mpl
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(
fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.plot_sources(evoked, exclude=[0])
ica.exclude = [0]
ica.plot_sources(evoked) # does the same thing
assert_raises(ValueError, ica.plot_sources, 'meeow')
plt.close('all')
def test_clickable_image():
"""Test the ClickableImage class."""
# Gen data and create clickable image
im = np.random.RandomState(0).randn(100, 100)
clk = ClickableImage(im)
clicks = [(12, 8), (46, 48), (10, 24)]
# Generate clicks
for click in clicks:
_fake_click(clk.fig, clk.ax, click, xform='data')
assert_allclose(np.array(clicks), np.array(clk.coords))
assert (len(clicks) == len(clk.coords))
# Exporting to layout
lt = clk.to_layout()
assert (lt.pos.shape[0] == len(clicks))
assert_allclose(lt.pos[1, 0] / lt.pos[2, 0],
clicks[1][0] / float(clicks[2][0]))
clk.plot_clicks()
plt.close('all')
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
import matplotlib.pyplot as plt
res = 8
fast_test = {"res": res, "contours": 0, "sensors": False}
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2,
max_pca_components=3, n_pca_components=3)
ica_picks = _get_picks(raw)
with warnings.catch_warnings(record=True):
ica.fit(raw, picks=ica_picks)
warnings.simplefilter('always', UserWarning)
with warnings.catch_warnings(record=True):
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components, image_interp='bilinear',
colorbar=True, **fast_test)
# test interactive mode (passing 'inst' arg)
plt.close('all')
ica.plot_components([0, 1], image_interp='bilinear', inst=raw, res=16)
fig = plt.gcf()
ax = [a for a in fig.get_children() if isinstance(a, plt.Axes)]
lbl = ax[1].get_label()
_fake_click(fig, ax[1], (0., 0.), xform='data')
c_fig = plt.gcf()
ax = [a for a in c_fig.get_children() if isinstance(a, plt.Axes)]
labels = [a.get_label() for a in ax]
for l in ['topomap', 'image', 'erp', 'spectrum', 'variance']:
assert_true(l in labels)
topomap_ax = ax[labels.index('topomap')]
title = topomap_ax.get_title()
assert_true(lbl == title)
ica.info = None
assert_raises(ValueError, ica.plot_components, 1)
assert_raises(RuntimeError, ica.plot_components, 1, ch_type='mag')
plt.close('all')
def test_plot_instance_components():
"""Test plotting of components as instances of raw and epochs."""
import matplotlib.pyplot as plt
raw = _get_raw()
picks = _get_picks(raw)
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2, max_pca_components=3, n_pca_components=3)
with warnings.catch_warnings(record=True): # bad proj
ica.fit(raw, picks=picks)
fig = ica.plot_sources(raw, exclude=[0], title="Components")
fig.canvas.key_press_event("down")
fig.canvas.key_press_event("up")
fig.canvas.key_press_event("right")
fig.canvas.key_press_event("left")
fig.canvas.key_press_event("o")
fig.canvas.key_press_event("-")
fig.canvas.key_press_event("+")
fig.canvas.key_press_event("=")
fig.canvas.key_press_event("pageup")
fig.canvas.key_press_event("pagedown")
fig.canvas.key_press_event("home")
fig.canvas.key_press_event("end")
fig.canvas.key_press_event("f11")
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], "data")
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event("escape")
plt.close("all")
epochs = _get_epochs()
fig = ica.plot_sources(epochs, exclude=[0], title="Components")
fig.canvas.key_press_event("down")
fig.canvas.key_press_event("up")
fig.canvas.key_press_event("right")
fig.canvas.key_press_event("left")
fig.canvas.key_press_event("o")
fig.canvas.key_press_event("-")
fig.canvas.key_press_event("+")
fig.canvas.key_press_event("=")
fig.canvas.key_press_event("pageup")
fig.canvas.key_press_event("pagedown")
fig.canvas.key_press_event("home")
fig.canvas.key_press_event("end")
fig.canvas.key_press_event("f11")
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], "data")
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event("escape")
plt.close("all")
def test_plot_instance_components():
"""Test plotting of components as instances of raw and epochs."""
import matplotlib.pyplot as plt
raw = _get_raw()
picks = _get_picks(raw)
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2,
max_pca_components=3, n_pca_components=3)
with warnings.catch_warnings(record=True): # bad proj
ica.fit(raw, picks=picks)
fig = ica.plot_sources(raw, exclude=[0], title='Components')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.key_press_event('right')
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('o')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event('=')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event('pagedown')
fig.canvas.key_press_event('home')
fig.canvas.key_press_event('end')
fig.canvas.key_press_event('f11')
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
epochs = _get_epochs()
fig = ica.plot_sources(epochs, exclude=[0], title='Components')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.key_press_event('right')
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('o')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event('=')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event('pagedown')
fig.canvas.key_press_event('home')
fig.canvas.key_press_event('end')
fig.canvas.key_press_event('f11')
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [-0.1, 0.9]) # click on y-label
fig.canvas.key_press_event('escape')
plt.close('all')
def _add_annotation(raw_fig):
"""Add an Annotation to a Raw plot."""
data_ax = raw_fig.mne.ax_main
raw_fig.canvas.key_press_event('a') # Toggle Annotation mode
ann_fig = raw_fig.mne.fig_annotation
for key in 'test': # Annotation will be named: BAD_test
ann_fig.canvas.key_press_event(key)
ann_fig.canvas.key_press_event('enter')
# Draw a 4 second long Annotation.
_fake_click(raw_fig,
data_ax, [1., 1.],
xform='data',
button=1,
kind='press')
_fake_click(raw_fig,
data_ax, [5., 1.],
xform='data',
button=1,
kind='motion')
_fake_click(raw_fig,
data_ax, [5., 1.],
xform='data',
button=1,
kind='release')
def test_plot_ica_sources():
"""Test plotting of ICA panel."""
raw = read_raw_fif(raw_fname).crop(0, 1).load_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
ecg=False,
eog=False,
exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
ica.exclude = [1]
fig = ica.plot_sources(raw)
fig.canvas.key_press_event('escape')
# Sadly close_event isn't called on Agg backend and the test always passes.
assert_array_equal(ica.exclude, [1])
plt.close('all')
# dtype can change int->np.int after load, test it explicitly
ica.n_components_ = np.int64(ica.n_components_)
fig = ica.plot_sources(raw)
# also test mouse clicks
data_ax = fig.axes[0]
assert len(plt.get_fignums()) == 1
_fake_click(fig, data_ax, [-0.1, 0.9]) # click on y-label
assert len(plt.get_fignums()) == 2
ica.exclude = [1]
ica.plot_sources(raw)
raw.info['bads'] = ['MEG 0113']
with pytest.raises(RuntimeError, match="Raw doesn't match fitted data"):
ica.plot_sources(inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
with pytest.raises(RuntimeError, match="Epochs don't match fitted data"):
ica.plot_sources(inst=epochs)
epochs.info['bads'] = []
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax, [line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax, [ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.exclude = [0]
ica.plot_sources(evoked)
ica.labels_ = dict(eog=[0])
ica.labels_['eog/0/crazy-channel'] = [0]
ica.plot_sources(evoked) # now with labels
with pytest.raises(ValueError, match='must be of Raw or Epochs type'):
ica.plot_sources('meeow')
plt.close('all')
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
import matplotlib.pyplot as plt
res = 8
fast_test = {"res": res, "contours": 0, "sensors": False}
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname),
n_components=2,
max_pca_components=3,
n_pca_components=3)
ica_picks = _get_picks(raw)
with warnings.catch_warnings(record=True):
ica.fit(raw, picks=ica_picks)
warnings.simplefilter('always', UserWarning)
with warnings.catch_warnings(record=True):
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components,
image_interp='bilinear',
colorbar=True,
**fast_test)
plt.close('all')
# test interactive mode (passing 'inst' arg)
ica.plot_components([0, 1], image_interp='bilinear', inst=raw, res=16)
fig = plt.gcf()
# test title click
# ----------------
lbl = fig.axes[1].get_label()
ica_idx = int(lbl[-3:])
titles = [ax.title for ax in fig.axes]
title_pos_midpoint = (titles[1].get_window_extent().extents.reshape(
(2, 2)).mean(axis=0))
# first click adds to exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx in ica.exclude
# clicking again removes from exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx not in ica.exclude
# test topo click
# ---------------
_fake_click(fig, fig.axes[1], (0., 0.), xform='data')
c_fig = plt.gcf()
labels = [ax.get_label() for ax in c_fig.axes]
for l in ['topomap', 'image', 'erp', 'spectrum', 'variance']:
assert_true(l in labels)
topomap_ax = c_fig.axes[labels.index('topomap')]
title = topomap_ax.get_title()
assert_true(lbl == title)
ica.info = None
assert_raises(ValueError, ica.plot_components, 1)
assert_raises(RuntimeError, ica.plot_components, 1, ch_type='mag')
plt.close('all')
def test_plot_volume_source_estimates():
"""Test interactive plotting of volume source estimates."""
forward = read_forward_solution(fwd_fname)
sample_src = forward['src']
vertices = [s['vertno'] for s in sample_src]
n_verts = sum(len(v) for v in vertices)
n_time = 2
data = np.random.RandomState(0).rand(n_verts, n_time)
vol_stc = VolSourceEstimate(data, vertices, 1, 1)
vol_vec_stc = VolVectorSourceEstimate(
np.tile(vol_stc.data[:, np.newaxis], (1, 3, 1)), vol_stc.vertices, 0,
1)
for mode, stc in zip(['glass_brain', 'stat_map'], (vol_stc, vol_vec_stc)):
with pytest.warns(None): # sometimes get scalars/index warning
fig = stc.plot(sample_src,
subject='sample',
subjects_dir=subjects_dir,
mode=mode)
# [ax_time, ax_y, ax_x, ax_z]
for ax_idx in [0, 2, 3, 4]:
_fake_click(fig, fig.axes[ax_idx], (0.3, 0.5))
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('shift+right')
with pytest.raises(ValueError, match='must be one of'):
vol_stc.plot(sample_src, 'sample', subjects_dir, mode='abcd')
vertices.append([])
surface_stc = SourceEstimate(data, vertices, 1, 1)
with pytest.raises(ValueError, match='Only Vol'):
plot_volume_source_estimates(surface_stc, sample_src, 'sample',
subjects_dir)
with pytest.raises(ValueError, match='Negative colormap limits'):
vol_stc.plot(sample_src,
'sample',
subjects_dir,
clim=dict(lims=[-1, 2, 3], kind='value'))
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
import matplotlib.pyplot as plt
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2, max_pca_components=3, n_pca_components=3)
ica_picks = _get_picks(raw)
with warnings.catch_warnings(record=True):
ica.fit(raw, picks=ica_picks)
warnings.simplefilter("always", UserWarning)
with warnings.catch_warnings(record=True):
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components, image_interp="bilinear", res=16, colorbar=True)
# test interactive mode (passing 'inst' arg)
plt.close("all")
ica.plot_components([0, 1], image_interp="bilinear", res=16, inst=raw)
fig = plt.gcf()
ax = [a for a in fig.get_children() if isinstance(a, plt.Axes)]
lbl = ax[1].get_label()
_fake_click(fig, ax[1], (0.0, 0.0), xform="data")
c_fig = plt.gcf()
ax = [a for a in c_fig.get_children() if isinstance(a, plt.Axes)]
labels = [a.get_label() for a in ax]
for l in ["topomap", "image", "erp", "spectrum", "variance"]:
assert_true(l in labels)
topomap_ax = ax[labels.index("topomap")]
title = topomap_ax.get_title()
assert_true(lbl == title)
ica.info = None
assert_raises(ValueError, ica.plot_components, 1)
assert_raises(RuntimeError, ica.plot_components, 1, ch_type="mag")
plt.close("all")
def test_plot_topo_image_epochs():
"""Test plotting of epochs image topography."""
title = 'ERF images - MNE sample data'
epochs = _get_epochs()
epochs.load_data()
cmap = mne_analyze_colormap(format='matplotlib')
data_min = epochs._data.min()
plt.close('all')
fig = plot_topo_image_epochs(epochs, sigma=0.5, vmin=-200, vmax=200,
colorbar=True, title=title, cmap=cmap)
assert epochs._data.min() == data_min
num_figures_before = len(plt.get_fignums())
_fake_click(fig, fig.axes[0], (0.08, 0.64))
assert num_figures_before + 1 == len(plt.get_fignums())
# test for auto-showing a colorbar when only 1 sensor type
ep = epochs.copy().pick_types(meg=False, eeg=True)
fig = plot_topo_image_epochs(ep, vmin=None, vmax=None, colorbar=None,
cmap=cmap)
ax = [x for x in fig.get_children() if isinstance(x, matplotlib.axes.Axes)]
qm_cmap = [y.cmap for x in ax for y in x.get_children()
if isinstance(y, matplotlib.collections.QuadMesh)]
assert qm_cmap[0] is cmap
plt.close('all')
def test_plot_topo_image_epochs():
"""Test plotting of epochs image topography."""
title = 'ERF images - MNE sample data'
epochs = _get_epochs()
epochs.load_data()
cmap = mne_analyze_colormap(format='matplotlib')
data_min = epochs._data.min()
plt.close('all')
fig = plot_topo_image_epochs(epochs, sigma=0.5, vmin=-200, vmax=200,
colorbar=True, title=title, cmap=cmap)
assert epochs._data.min() == data_min
num_figures_before = len(plt.get_fignums())
_fake_click(fig, fig.axes[0], (0.08, 0.64))
assert num_figures_before + 1 == len(plt.get_fignums())
# test for auto-showing a colorbar when only 1 sensor type
ep = epochs.copy().pick_types(meg=False, eeg=True)
fig = plot_topo_image_epochs(ep, vmin=None, vmax=None, colorbar=None,
cmap=cmap)
ax = [x for x in fig.get_children() if isinstance(x, matplotlib.axes.Axes)]
qm_cmap = [y.cmap for x in ax for y in x.get_children()
if isinstance(y, matplotlib.collections.QuadMesh)]
assert qm_cmap[0] is cmap
plt.close('all')
def test_plot_ica_sources():
"""Test plotting of ICA panel
"""
import matplotlib.pyplot as plt
raw = io.Raw(raw_fname, preload=False)
raw.crop(0, 1, copy=False)
raw.preload_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info, meg=True, eeg=False, stim=False,
ecg=False, eog=False, exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
raw.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
assert_raises(RuntimeError, ica.plot_sources, inst=epochs)
epochs.info['bads'] = []
with warnings.catch_warnings(record=True): # no labeled objects mpl
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.plot_sources(evoked, exclude=[0])
ica.exclude = [0]
ica.plot_sources(evoked) # does the same thing
assert_raises(ValueError, ica.plot_sources, 'meeow')
plt.close('all')
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
res = 8
fast_test = {"res": res, "contours": 0, "sensors": False}
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2)
ica_picks = _get_picks(raw)
with pytest.warns(RuntimeWarning, match='projection'):
ica.fit(raw, picks=ica_picks)
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components, image_interp='bilinear',
colorbar=True, **fast_test)
plt.close('all')
# test interactive mode (passing 'inst' arg)
with catch_logging() as log:
ica.plot_components([0, 1], image_interp='bilinear', inst=raw, res=16,
verbose='debug', ch_type='grad')
log = log.getvalue()
assert 'grad data' in log
assert 'Interpolation mode local to mean' in log
fig = plt.gcf()
# test title click
# ----------------
lbl = fig.axes[1].get_label()
ica_idx = int(lbl[-3:])
titles = [ax.title for ax in fig.axes]
title_pos_midpoint = (titles[1].get_window_extent().extents
.reshape((2, 2)).mean(axis=0))
# first click adds to exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx in ica.exclude
# clicking again removes from exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx not in ica.exclude
# test topo click
# ---------------
_fake_click(fig, fig.axes[1], (0., 0.), xform='data')
c_fig = plt.gcf()
labels = [ax.get_label() for ax in c_fig.axes]
for label in ['topomap', 'image', 'erp', 'spectrum', 'variance']:
assert label in labels
topomap_ax = c_fig.axes[labels.index('topomap')]
title = topomap_ax.get_title()
assert (lbl == title)
ica.info = None
with pytest.raises(RuntimeError, match='fit the ICA'):
ica.plot_components(1, ch_type='mag')
def test_plot_ica_components():
"""Test plotting of ICA solutions."""
import matplotlib.pyplot as plt
res = 8
fast_test = {"res": res, "contours": 0, "sensors": False}
raw = _get_raw()
ica = ICA(noise_cov=read_cov(cov_fname), n_components=2,
max_pca_components=3, n_pca_components=3)
ica_picks = _get_picks(raw)
with warnings.catch_warnings(record=True):
ica.fit(raw, picks=ica_picks)
warnings.simplefilter('always', UserWarning)
with warnings.catch_warnings(record=True):
for components in [0, [0], [0, 1], [0, 1] * 2, None]:
ica.plot_components(components, image_interp='bilinear',
colorbar=True, **fast_test)
plt.close('all')
# test interactive mode (passing 'inst' arg)
ica.plot_components([0, 1], image_interp='bilinear', inst=raw, res=16)
fig = plt.gcf()
# test title click
# ----------------
lbl = fig.axes[1].get_label()
ica_idx = int(lbl[-3:])
titles = [ax.title for ax in fig.axes]
title_pos_midpoint = (titles[1].get_window_extent().extents
.reshape((2, 2)).mean(axis=0))
# first click adds to exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx in ica.exclude
# clicking again removes from exclude
_fake_click(fig, fig.axes[1], title_pos_midpoint, xform='pix')
assert ica_idx not in ica.exclude
# test topo click
# ---------------
_fake_click(fig, fig.axes[1], (0., 0.), xform='data')
c_fig = plt.gcf()
labels = [ax.get_label() for ax in c_fig.axes]
for l in ['topomap', 'image', 'erp', 'spectrum', 'variance']:
assert_true(l in labels)
topomap_ax = c_fig.axes[labels.index('topomap')]
title = topomap_ax.get_title()
assert_true(lbl == title)
ica.info = None
assert_raises(ValueError, ica.plot_components, 1)
assert_raises(RuntimeError, ica.plot_components, 1, ch_type='mag')
plt.close('all')
def test_plot_ica_sources():
"""Test plotting of ICA panel."""
raw = read_raw_fif(raw_fname).crop(0, 1).load_data()
picks = _get_picks(raw)
epochs = _get_epochs()
raw.pick_channels([raw.ch_names[k] for k in picks])
ica_picks = pick_types(raw.info, meg=True, eeg=False, stim=False,
ecg=False, eog=False, exclude='bads')
ica = ICA(n_components=2, max_pca_components=3, n_pca_components=3)
ica.fit(raw, picks=ica_picks)
ica.exclude = [1]
fig = ica.plot_sources(raw)
fig.canvas.key_press_event('escape')
# Sadly close_event isn't called on Agg backend and the test always passes.
assert_array_equal(ica.exclude, [1])
plt.close('all')
# dtype can change int->np.int after load, test it explicitly
ica.n_components_ = np.int64(ica.n_components_)
fig = ica.plot_sources(raw, [1])
# also test mouse clicks
data_ax = fig.axes[0]
_fake_click(fig, data_ax, [-0.1, 0.9]) # click on y-label
raw.info['bads'] = ['MEG 0113']
pytest.raises(RuntimeError, ica.plot_sources, inst=raw)
ica.plot_sources(epochs)
epochs.info['bads'] = ['MEG 0113']
pytest.raises(RuntimeError, ica.plot_sources, inst=epochs)
epochs.info['bads'] = []
ica.plot_sources(epochs.average())
evoked = epochs.average()
fig = ica.plot_sources(evoked)
# Test a click
ax = fig.get_axes()[0]
line = ax.lines[0]
_fake_click(fig, ax,
[line.get_xdata()[0], line.get_ydata()[0]], 'data')
_fake_click(fig, ax,
[ax.get_xlim()[0], ax.get_ylim()[1]], 'data')
# plot with bad channels excluded
ica.plot_sources(evoked, exclude=[0])
ica.exclude = [0]
ica.plot_sources(evoked) # does the same thing
ica.labels_ = dict(eog=[0])
ica.labels_['eog/0/crazy-channel'] = [0]
ica.plot_sources(evoked) # now with labels
pytest.raises(ValueError, ica.plot_sources, 'meeow')
plt.close('all')
def test_plot_topo_single_ch():
"""Test single channel topoplot with time cursor"""
import matplotlib.pyplot as plt
evoked = _get_epochs().average()
fig = plot_evoked_topo(evoked)
num_figures_before = len(plt.get_fignums())
_fake_click(fig, fig.axes[0], (0.08, 0.65))
assert_equal(num_figures_before + 1, len(plt.get_fignums()))
fig = plt.gcf()
ax = plt.gca()
_fake_click(fig, ax, (.5, .5), kind='motion') # cursor should appear
assert_true(isinstance(ax._cursorline, matplotlib.lines.Line2D))
_fake_click(fig, ax, (1.5, 1.5), kind='motion') # cursor should disappear
assert_equal(ax._cursorline, None)
plt.close('all')
def test_plot_topo_single_ch():
"""Test single channel topoplot with time cursor."""
evoked = _get_epochs().average()
fig = plot_evoked_topo(evoked, background_color='w')
# test status bar message
ax = plt.gca()
assert ('MEG 0113' in ax.format_coord(.065, .63))
num_figures_before = len(plt.get_fignums())
_fake_click(fig, fig.axes[0], (0.08, 0.65))
assert num_figures_before + 1 == len(plt.get_fignums())
fig = plt.gcf()
ax = plt.gca()
_fake_click(fig, ax, (.5, .5), kind='motion') # cursor should appear
assert (isinstance(ax._cursorline, matplotlib.lines.Line2D))
_fake_click(fig, ax, (1.5, 1.5), kind='motion') # cursor should disappear
assert ax._cursorline is None
plt.close('all')
def test_plot_raw():
"""Test plotting of raw data."""
import matplotlib.pyplot as plt
raw = _get_raw()
events = _get_events()
plt.close('all') # ensure all are closed
with warnings.catch_warnings(record=True):
fig = raw.plot(events=events, show_options=True)
# test mouse clicks
x = fig.get_axes()[0].lines[1].get_xdata().mean()
y = fig.get_axes()[0].lines[1].get_ydata().mean()
data_ax = fig.get_axes()[0]
_fake_click(fig, data_ax, [x, y], xform='data') # mark a bad channel
_fake_click(fig, data_ax, [x, y], xform='data') # unmark a bad channel
_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, fig.get_axes()[1], [0.5, 0.5]) # change time
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
_fake_click(fig, fig.get_axes()[3], [0.5, 0.5]) # open SSP window
fig.canvas.button_press_event(1, 1, 1) # outside any axes
fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up
# sadly these fail when no renderer is used (i.e., when using Agg):
# ssp_fig = set(plt.get_fignums()) - set([fig.number])
# assert_equal(len(ssp_fig), 1)
# ssp_fig = plt.figure(list(ssp_fig)[0])
# ax = ssp_fig.get_axes()[0] # only one axis is used
# t = [c for c in ax.get_children() if isinstance(c,
# matplotlib.text.Text)]
# pos = np.array(t[0].get_position()) + 0.01
# _fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # off
# _fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # on
# test keypresses
fig.canvas.key_press_event('escape')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.key_press_event('right')
fig.canvas.key_press_event('left')
fig.canvas.key_press_event('o')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event('=')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event('pagedown')
fig.canvas.key_press_event('home')
fig.canvas.key_press_event('end')
fig.canvas.key_press_event('?')
fig.canvas.key_press_event('f11')
fig.canvas.key_press_event('escape')
# Color setting
assert_raises(KeyError, raw.plot, event_color={0: 'r'})
assert_raises(TypeError, raw.plot, event_color={'foo': 'r'})
annot = Annotations([10, 10 + raw.first_samp / raw.info['sfreq']],
[10, 10], ['test', 'test'], raw.info['meas_date'])
raw.annotations = annot
fig = plot_raw(raw, events=events, event_color={-1: 'r', 998: 'b'})
plt.close('all')
for order in ['position', 'selection', range(len(raw.ch_names))[::-1],
[1, 2, 4, 6]]:
fig = raw.plot(order=order)
x = fig.get_axes()[0].lines[1].get_xdata()[10]
y = fig.get_axes()[0].lines[1].get_ydata()[10]
_fake_click(fig, data_ax, [x, y], xform='data') # mark bad
fig.canvas.key_press_event('down') # change selection
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
if order == 'position': # test clicking topo to change selection
sel_fig = plt.figure(1)
topo_ax = sel_fig.axes[1]
_fake_click(sel_fig, topo_ax, [-0.425, 0.20223853],
xform='data')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.scroll_event(0.5, 0.5, -1) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 1) # scroll up
plt.close('all')
def test_plot_sensors():
"""Test plotting of sensor array."""
raw = _get_raw()
plt.close('all')
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap',
ch_type='mag',
show_names=['MEG 0111', 'MEG 0131'])
plt.close('all')
ax = plt.subplot(111)
raw.plot_sensors(ch_groups='position', axes=ax)
raw.plot_sensors(ch_groups='selection', to_sphere=False)
raw.plot_sensors(ch_groups=[[0, 1, 2], [3, 4]])
pytest.raises(ValueError, raw.plot_sensors, ch_groups='asd')
pytest.raises(TypeError, plot_sensors, raw) # needs to be info
pytest.raises(ValueError, plot_sensors, raw.info, kind='sasaasd')
plt.close('all')
fig, sels = raw.plot_sensors('select', show_names=True)
ax = fig.axes[0]
# Click with no sensors
_fake_click(fig, ax, (0., 0.), xform='data')
_fake_click(fig, ax, (0, 0.), xform='data', kind='release')
assert len(fig.lasso.selection) == 0
# Lasso with 1 sensor
_fake_click(fig, ax, (-0.5, 0.5), xform='data')
plt.draw()
_fake_click(fig, ax, (0., 0.5), xform='data', kind='motion')
_fake_click(fig, ax, (0., 0.), xform='data', kind='motion')
fig.canvas.key_press_event('control')
_fake_click(fig, ax, (-0.5, 0.), xform='data', kind='release')
assert len(fig.lasso.selection) == 1
_fake_click(fig, ax, (-0.09, -0.43), xform='data') # single selection
assert len(fig.lasso.selection) == 2
_fake_click(fig, ax, (-0.09, -0.43), xform='data') # deselect
assert len(fig.lasso.selection) == 1
plt.close('all')
def test_plot():
"""Test TFR plotting."""
data = np.zeros((3, 2, 3))
times = np.array([.1, .2, .3])
freqs = np.array([.10, .20])
info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
['mag', 'mag', 'mag'])
tfr = AverageTFR(info,
data=data,
times=times,
freqs=freqs,
nave=20,
comment='test',
method='crazy-tfr')
tfr.plot([1, 2],
title='title',
colorbar=False,
mask=np.ones(tfr.data.shape[1:], bool))
plt.close('all')
ax = plt.subplot2grid((2, 2), (0, 0))
ax2 = plt.subplot2grid((2, 2), (1, 1))
ax3 = plt.subplot2grid((2, 2), (0, 1))
tfr.plot(picks=[0, 1, 2], axes=[ax, ax2, ax3])
plt.close('all')
tfr.plot([1, 2], title='title', colorbar=False, exclude='bads')
plt.close('all')
tfr.plot_topo(picks=[1, 2])
plt.close('all')
fig = tfr.plot(picks=[1], cmap='RdBu_r') # interactive mode on by default
fig.canvas.key_press_event('up')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('+')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('-')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('pageup')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('pagedown')
cbar = fig.get_axes()[0].CB # Fake dragging with mouse.
ax = cbar.cbar.ax
_fake_click(fig, ax, (0.1, 0.1))
_fake_click(fig, ax, (0.1, 0.2), kind='motion')
_fake_click(fig, ax, (0.1, 0.3), kind='release')
_fake_click(fig, ax, (0.1, 0.1), button=3)
_fake_click(fig, ax, (0.1, 0.2), button=3, kind='motion')
_fake_click(fig, ax, (0.1, 0.3), kind='release')
fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up
plt.close('all')
def test_plot():
"""Test TFR plotting."""
data = np.zeros((3, 2, 3))
times = np.array([.1, .2, .3])
freqs = np.array([.10, .20])
info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
['mag', 'mag', 'mag'])
tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
nave=20, comment='test', method='crazy-tfr')
tfr.plot([1, 2], title='title', colorbar=False,
mask=np.ones(tfr.data.shape[1:], bool))
plt.close('all')
ax = plt.subplot2grid((2, 2), (0, 0))
ax2 = plt.subplot2grid((2, 2), (1, 1))
ax3 = plt.subplot2grid((2, 2), (0, 1))
tfr.plot(picks=[0, 1, 2], axes=[ax, ax2, ax3])
plt.close('all')
tfr.plot([1, 2], title='title', colorbar=False, exclude='bads')
plt.close('all')
tfr.plot_topo(picks=[1, 2])
plt.close('all')
fig = tfr.plot(picks=[1], cmap='RdBu_r') # interactive mode on by default
fig.canvas.key_press_event('up')
fig.canvas.key_press_event(' ')
fig.canvas.key_press_event('down')
cbar = fig.get_axes()[0].CB # Fake dragging with mouse.
ax = cbar.cbar.ax
_fake_click(fig, ax, (0.1, 0.1))
_fake_click(fig, ax, (0.1, 0.2), kind='motion')
_fake_click(fig, ax, (0.1, 0.3), kind='release')
_fake_click(fig, ax, (0.1, 0.1), button=3)
_fake_click(fig, ax, (0.1, 0.2), button=3, kind='motion')
_fake_click(fig, ax, (0.1, 0.3), kind='release')
fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up
plt.close('all')
def test_plot_raw():
"""Test plotting of raw data."""
raw = _get_raw()
raw.info['lowpass'] = 10. # allow heavy decim during plotting
events = _get_events()
plt.close('all') # ensure all are closed
assert len(plt.get_fignums()) == 0
fig = raw.plot(events=events, order=[1, 7, 3], group_by='original')
assert len(plt.get_fignums()) == 1
# make sure fig._mne_params is present
assert isinstance(fig._mne_params, dict)
# test mouse clicks
x = fig.get_axes()[0].lines[1].get_xdata().mean()
y = fig.get_axes()[0].lines[1].get_ydata().mean()
data_ax = fig.axes[0]
_fake_click(fig, data_ax, [x, y], xform='data') # mark a bad channel
_fake_click(fig, data_ax, [x, y], xform='data') # unmark a bad channel
_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, fig.get_axes()[1], [0.5, 0.5]) # change time
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
assert len(plt.get_fignums()) == 1
# open SSP window
_fake_click(fig, fig.get_axes()[-1], [0.5, 0.5])
_fake_click(fig, fig.get_axes()[-1], [0.5, 0.5], kind='release')
assert len(plt.get_fignums()) == 2
ssp_fig = plt.figure(plt.get_fignums()[-1])
fig.canvas.button_press_event(1, 1, 1) # outside any axes
fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up
ax = ssp_fig.get_axes()[0] # only one axis is used
assert _proj_status(ax) == [True] * 3
t = [c for c in ax.get_children() if isinstance(c, matplotlib.text.Text)]
pos = np.array(t[0].get_position()) + 0.01
_fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # off
assert _proj_status(ax) == [False, True, True]
_fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # on
assert _proj_status(ax) == [True] * 3
_fake_click(ssp_fig, ssp_fig.get_axes()[1], [0.5, 0.5]) # all off
_fake_click(ssp_fig, ssp_fig.get_axes()[1], [0.5, 0.5], kind='release')
assert _proj_status(ax) == [False] * 3
_fake_click(ssp_fig, ssp_fig.get_axes()[1], [0.5, 0.5]) # all on
_fake_click(ssp_fig, ssp_fig.get_axes()[1], [0.5, 0.5], kind='release')
assert _proj_status(ax) == [True] * 3
# test keypresses
# test for group_by='original'
for key in [
'down', 'up', 'right', 'left', 'o', '-', '+', '=', 'd', 'd',
'pageup', 'pagedown', 'home', 'end', '?', 'f11', 'z', 'escape'
]:
fig.canvas.key_press_event(key)
# test for group_by='selection'
fig = plot_raw(raw, events=events, group_by='selection')
for key in [
'b', 'down', 'up', 'right', 'left', 'o', '-', '+', '=', 'd', 'd',
'pageup', 'pagedown', 'home', 'end', '?', 'f11', 'b', 'z', 'escape'
]:
fig.canvas.key_press_event(key)
# test zen mode
fig = plot_raw(raw, show_scrollbars=False)
# Color setting
pytest.raises(KeyError, raw.plot, event_color={0: 'r'})
pytest.raises(TypeError, raw.plot, event_color={'foo': 'r'})
annot = Annotations([10, 10 + raw.first_samp / raw.info['sfreq']],
[10, 10], ['test', 'test'], raw.info['meas_date'])
with pytest.warns(RuntimeWarning, match='outside data range'):
raw.set_annotations(annot)
fig = plot_raw(raw, events=events, event_color={-1: 'r', 998: 'b'})
plt.close('all')
for group_by, order in zip(
['position', 'selection'],
[np.arange(len(raw.ch_names))[::-3], [1, 2, 4, 6]]):
with pytest.warns(None): # sometimes projection
fig = raw.plot(group_by=group_by, order=order)
x = fig.get_axes()[0].lines[1].get_xdata()[10]
y = fig.get_axes()[0].lines[1].get_ydata()[10]
with pytest.warns(None): # old mpl (at least 2.0) can warn
_fake_click(fig, data_ax, [x, y], xform='data') # mark bad
fig.canvas.key_press_event('down') # change selection
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
sel_fig = plt.figure(1)
topo_ax = sel_fig.axes[1]
_fake_click(sel_fig, topo_ax, [-0.425, 0.20223853], xform='data')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.scroll_event(0.5, 0.5, -1) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 1) # scroll up
_fake_click(sel_fig, topo_ax, [-0.5, 0.], xform='data')
_fake_click(sel_fig, topo_ax, [0.5, 0.], xform='data', kind='motion')
_fake_click(sel_fig, topo_ax, [0.5, 0.5], xform='data', kind='motion')
_fake_click(sel_fig,
topo_ax, [-0.5, 0.5],
xform='data',
kind='release')
plt.close('all')
# test if meas_date has only one element
raw.info['meas_date'] = (raw.info['meas_date'][0], 0)
annot = Annotations([1 + raw.first_samp / raw.info['sfreq']], [5], ['bad'])
with pytest.warns(RuntimeWarning, match='outside data range'):
raw.set_annotations(annot)
with pytest.warns(None): # sometimes projection
raw.plot(group_by='position', order=np.arange(8))
for fig_num in plt.get_fignums():
fig = plt.figure(fig_num)
if hasattr(fig, 'radio'): # Get access to selection fig.
break
for key in ['down', 'up', 'escape']:
fig.canvas.key_press_event(key)
plt.close('all')
def test_plot_raw():
"""Test plotting of raw data."""
import matplotlib.pyplot as plt
raw = _get_raw()
raw.info['lowpass'] = 10. # allow heavy decim during plotting
events = _get_events()
plt.close('all') # ensure all are closed
with warnings.catch_warnings(record=True):
fig = raw.plot(events=events, show_options=True, order=[1, 7, 3],
group_by='original')
# test mouse clicks
x = fig.get_axes()[0].lines[1].get_xdata().mean()
y = fig.get_axes()[0].lines[1].get_ydata().mean()
data_ax = fig.axes[0]
_fake_click(fig, data_ax, [x, y], xform='data') # mark a bad channel
_fake_click(fig, data_ax, [x, y], xform='data') # unmark a bad channel
_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, fig.get_axes()[1], [0.5, 0.5]) # change time
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
_fake_click(fig, fig.get_axes()[3], [0.5, 0.5]) # open SSP window
fig.canvas.button_press_event(1, 1, 1) # outside any axes
fig.canvas.scroll_event(0.5, 0.5, -0.5) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 0.5) # scroll up
# sadly these fail when no renderer is used (i.e., when using Agg):
# ssp_fig = set(plt.get_fignums()) - set([fig.number])
# assert_equal(len(ssp_fig), 1)
# ssp_fig = plt.figure(list(ssp_fig)[0])
# ax = ssp_fig.get_axes()[0] # only one axis is used
# t = [c for c in ax.get_children() if isinstance(c,
# matplotlib.text.Text)]
# pos = np.array(t[0].get_position()) + 0.01
# _fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # off
# _fake_click(ssp_fig, ssp_fig.get_axes()[0], pos, xform='data') # on
# test keypresses
for key in ['down', 'up', 'right', 'left', 'o', '-', '+', '=',
'pageup', 'pagedown', 'home', 'end', '?', 'f11', 'escape']:
fig.canvas.key_press_event(key)
fig = plot_raw(raw, events=events, group_by='selection')
for key in ['b', 'down', 'up', 'right', 'left', 'o', '-', '+', '=',
'pageup', 'pagedown', 'home', 'end', '?', 'f11', 'b',
'escape']:
fig.canvas.key_press_event(key)
# Color setting
assert_raises(KeyError, raw.plot, event_color={0: 'r'})
assert_raises(TypeError, raw.plot, event_color={'foo': 'r'})
annot = Annotations([10, 10 + raw.first_samp / raw.info['sfreq']],
[10, 10], ['test', 'test'], raw.info['meas_date'])
raw.annotations = annot
fig = plot_raw(raw, events=events, event_color={-1: 'r', 998: 'b'})
plt.close('all')
for group_by, order in zip(['position', 'selection'],
[np.arange(len(raw.ch_names))[::-3],
[1, 2, 4, 6]]):
fig = raw.plot(group_by=group_by, order=order)
x = fig.get_axes()[0].lines[1].get_xdata()[10]
y = fig.get_axes()[0].lines[1].get_ydata()[10]
_fake_click(fig, data_ax, [x, y], xform='data') # mark bad
fig.canvas.key_press_event('down') # change selection
_fake_click(fig, fig.get_axes()[2], [0.5, 0.5]) # change channels
sel_fig = plt.figure(1)
topo_ax = sel_fig.axes[1]
_fake_click(sel_fig, topo_ax, [-0.425, 0.20223853],
xform='data')
fig.canvas.key_press_event('down')
fig.canvas.key_press_event('up')
fig.canvas.scroll_event(0.5, 0.5, -1) # scroll down
fig.canvas.scroll_event(0.5, 0.5, 1) # scroll up
_fake_click(sel_fig, topo_ax, [-0.5, 0.], xform='data')
_fake_click(sel_fig, topo_ax, [0.5, 0.], xform='data',
kind='motion')
_fake_click(sel_fig, topo_ax, [0.5, 0.5], xform='data',
kind='motion')
_fake_click(sel_fig, topo_ax, [-0.5, 0.5], xform='data',
kind='release')
plt.close('all')
# test if meas_date has only one element
raw.info['meas_date'] = np.array([raw.info['meas_date'][0]],
dtype=np.int32)
raw.annotations = Annotations([1 + raw.first_samp / raw.info['sfreq']],
[5], ['bad'])
raw.plot(group_by='position', order=np.arange(8))
for fig_num in plt.get_fignums():
fig = plt.figure(fig_num)
if hasattr(fig, 'radio'): # Get access to selection fig.
break
for key in ['down', 'up', 'escape']:
fig.canvas.key_press_event(key)
plt.close('all')
def _annotation_helper(raw, events=False):
"""Test interactive annotations."""
# Some of our checks here require modern mpl to work properly
mpl_good_enough = LooseVersion(matplotlib.__version__) >= '2.0'
n_anns = len(raw.annotations)
plt.close('all')
if events:
events = np.array([[raw.first_samp + 100, 0, 1],
[raw.first_samp + 300, 0, 3]])
n_events = len(events)
else:
events = None
n_events = 0
fig = raw.plot(events=events)
assert len(plt.get_fignums()) == 1
data_ax = fig.axes[0]
fig.canvas.key_press_event('a') # annotation mode
assert len(plt.get_fignums()) == 2
# +2 from the scale bars
n_scale = 2
assert len(fig.axes[0].texts) == n_anns + n_events + n_scale
# modify description
ann_fig = plt.gcf()
for key in ' test':
ann_fig.canvas.key_press_event(key)
ann_fig.canvas.key_press_event('enter')
ann_fig = plt.gcf()
# XXX: _fake_click raises an error on Agg backend
_annotation_radio_clicked('', ann_fig.radio, data_ax.selector)
# draw annotation
fig.canvas.key_press_event('p') # use snap mode
_fake_click(fig, data_ax, [1., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='release')
assert len(raw.annotations.onset) == n_anns + 1
assert len(raw.annotations.duration) == n_anns + 1
assert len(raw.annotations.description) == n_anns + 1
assert raw.annotations.description[n_anns] == 'BAD_ test'
assert len(fig.axes[0].texts) == n_anns + 1 + n_events + n_scale
onset = raw.annotations.onset[n_anns]
want_onset = _sync_onset(raw, 1., inverse=True)
assert_allclose(onset, want_onset)
assert_allclose(raw.annotations.duration[n_anns], 4.)
# hover event
_fake_click(fig,
data_ax, [4.5, 1.],
xform='data',
button=None,
kind='motion')
_fake_click(fig,
data_ax, [4.7, 1.],
xform='data',
button=None,
kind='motion')
# modify annotation from end
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [2.5, 1.], xform='data', button=1, kind='motion')
_fake_click(fig,
data_ax, [2.5, 1.],
xform='data',
button=1,
kind='release')
if mpl_good_enough:
assert raw.annotations.onset[n_anns] == onset
assert_allclose(raw.annotations.duration[n_anns], 1.5)
# modify annotation from beginning
_fake_click(fig, data_ax, [1., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [0.5, 1.], xform='data', button=1, kind='motion')
_fake_click(fig,
data_ax, [0.5, 1.],
xform='data',
button=1,
kind='release')
if mpl_good_enough:
assert_allclose(raw.annotations.onset[n_anns], onset - 0.5, atol=1e-10)
assert_allclose(raw.annotations.duration[n_anns], 2.0)
assert len(raw.annotations.onset) == n_anns + 1
assert len(raw.annotations.duration) == n_anns + 1
assert len(raw.annotations.description) == n_anns + 1
assert raw.annotations.description[n_anns] == 'BAD_ test'
assert len(fig.axes[0].texts) == n_anns + 1 + n_events + n_scale
fig.canvas.key_press_event('shift+right')
assert len(fig.axes[0].texts) == n_scale
fig.canvas.key_press_event('shift+left')
assert len(fig.axes[0].texts) == n_anns + 1 + n_events + n_scale
# draw another annotation merging the two
_fake_click(fig, data_ax, [5.5, 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [2., 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [2., 1.], xform='data', button=1, kind='release')
# delete the annotation
assert len(raw.annotations.onset) == n_anns + 1
assert len(raw.annotations.duration) == n_anns + 1
assert len(raw.annotations.description) == n_anns + 1
if mpl_good_enough:
assert_allclose(raw.annotations.onset[n_anns], onset - 0.5, atol=1e-10)
assert_allclose(raw.annotations.duration[n_anns], 5.0)
assert len(fig.axes[0].texts) == n_anns + 1 + n_events + n_scale
# Delete
_fake_click(fig, data_ax, [1.5, 1.], xform='data', button=3, kind='press')
fig.canvas.key_press_event('a') # exit annotation mode
assert len(raw.annotations.onset) == n_anns
assert len(fig.axes[0].texts) == n_anns + n_events + n_scale
fig.canvas.key_press_event('shift+right')
assert len(fig.axes[0].texts) == n_scale
fig.canvas.key_press_event('shift+left')
assert len(fig.axes[0].texts) == n_anns + n_events + n_scale
plt.close('all')
def test_plot_sensors():
"""Test plotting of sensor array."""
import matplotlib.pyplot as plt
raw = _get_raw()
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap', ch_type='mag',
show_names=['MEG 0111', 'MEG 0131'])
plt.close('all')
ax = plt.subplot(111)
raw.plot_sensors(ch_groups='position', axes=ax)
raw.plot_sensors(ch_groups='selection', to_sphere=False)
raw.plot_sensors(ch_groups=[[0, 1, 2], [3, 4]])
assert_raises(ValueError, raw.plot_sensors, ch_groups='asd')
assert_raises(TypeError, plot_sensors, raw) # needs to be info
assert_raises(ValueError, plot_sensors, raw.info, kind='sasaasd')
plt.close('all')
fig, sels = raw.plot_sensors('select', show_names=True)
ax = fig.axes[0]
# Click with no sensors
_fake_click(fig, ax, (0., 0.), xform='data')
_fake_click(fig, ax, (0, 0.), xform='data', kind='release')
assert_equal(len(fig.lasso.selection), 0)
# Lasso with 1 sensor
_fake_click(fig, ax, (-0.5, 0.5), xform='data')
plt.draw()
_fake_click(fig, ax, (0., 0.5), xform='data', kind='motion')
_fake_click(fig, ax, (0., 0.), xform='data', kind='motion')
fig.canvas.key_press_event('control')
_fake_click(fig, ax, (-0.5, 0.), xform='data', kind='release')
assert_equal(len(fig.lasso.selection), 1)
_fake_click(fig, ax, (-0.09, -0.43), xform='data') # single selection
assert_equal(len(fig.lasso.selection), 2)
_fake_click(fig, ax, (-0.09, -0.43), xform='data') # deselect
assert_equal(len(fig.lasso.selection), 1)
plt.close('all')
def test_plot_sensors(raw):
"""Test plotting of sensor array."""
plt.close('all')
fig = raw.plot_sensors('3d')
_fake_click(fig, fig.gca(), (-0.08, 0.67))
raw.plot_sensors('topomap', ch_type='mag',
show_names=['MEG 0111', 'MEG 0131'])
plt.close('all')
ax = plt.subplot(111)
raw.plot_sensors(ch_groups='position', axes=ax)
raw.plot_sensors(ch_groups='selection', to_sphere=False)
raw.plot_sensors(ch_groups=[[0, 1, 2], [3, 4]])
pytest.raises(ValueError, raw.plot_sensors, ch_groups='asd')
pytest.raises(TypeError, plot_sensors, raw) # needs to be info
pytest.raises(ValueError, plot_sensors, raw.info, kind='sasaasd')
plt.close('all')
fig, sels = raw.plot_sensors('select', show_names=True)
ax = fig.axes[0]
# Click with no sensors
_fake_click(fig, ax, (0., 0.), xform='data')
_fake_click(fig, ax, (0, 0.), xform='data', kind='release')
assert fig.lasso.selection == []
# Lasso with 1 sensor (upper left)
_fake_click(fig, ax, (0, 1), xform='ax')
fig.canvas.draw()
assert fig.lasso.selection == []
_fake_click(fig, ax, (0.65, 1), xform='ax', kind='motion')
_fake_click(fig, ax, (0.65, 0.7), xform='ax', kind='motion')
fig.canvas.key_press_event('control')
_fake_click(fig, ax, (0, 0.7), xform='ax', kind='release')
assert fig.lasso.selection == ['MEG 0121']
# check that point appearance changes
fc = fig.lasso.collection.get_facecolors()
ec = fig.lasso.collection.get_edgecolors()
assert (fc[:, -1] == [0.5, 1., 0.5]).all()
assert (ec[:, -1] == [0.25, 1., 0.25]).all()
_fake_click(fig, ax, (0.7, 1), xform='ax', kind='motion')
xy = ax.collections[0].get_offsets()
_fake_click(fig, ax, xy[2], xform='data') # single selection
assert fig.lasso.selection == ['MEG 0121', 'MEG 0131']
_fake_click(fig, ax, xy[2], xform='data') # deselect
assert fig.lasso.selection == ['MEG 0121']
plt.close('all')
raw.info['dev_head_t'] = None # like empty room
with pytest.warns(RuntimeWarning, match='identity'):
raw.plot_sensors()
def _annotation_helper(raw):
"""Helper for testing interactive annotations."""
import matplotlib.pyplot as plt
n_anns = 0 if raw.annotations is None else len(raw.annotations.onset)
fig = raw.plot()
data_ax = fig.axes[0]
fig.canvas.key_press_event('a') # annotation mode
# modify description
ann_fig = plt.gcf()
for key in ' test':
ann_fig.canvas.key_press_event(key)
ann_fig.canvas.key_press_event('enter')
ann_fig = plt.gcf()
# XXX: _fake_click raises an error on Agg backend
_annotation_radio_clicked('', ann_fig.radio, data_ax.selector)
# draw annotation
_fake_click(fig, data_ax, [1., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='release')
# hover event
_fake_click(fig, data_ax, [4.5, 1.], xform='data', button=None,
kind='motion')
_fake_click(fig, data_ax, [4.7, 1.], xform='data', button=None,
kind='motion')
# modify annotation from end
_fake_click(fig, data_ax, [5., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [2.5, 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [2.5, 1.], xform='data', button=1,
kind='release')
# modify annotation from beginning
_fake_click(fig, data_ax, [1., 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [1.1, 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [1.1, 1.], xform='data', button=1,
kind='release')
assert_equal(len(raw.annotations.onset), n_anns + 1)
assert_equal(len(raw.annotations.duration), n_anns + 1)
assert_equal(len(raw.annotations.description), n_anns + 1)
assert_equal(raw.annotations.description[n_anns], 'BAD test')
# draw another annotation merging the two
_fake_click(fig, data_ax, [5.5, 1.], xform='data', button=1, kind='press')
_fake_click(fig, data_ax, [2., 1.], xform='data', button=1, kind='motion')
_fake_click(fig, data_ax, [2., 1.], xform='data', button=1, kind='release')
# delete the annotation
_fake_click(fig, data_ax, [1.5, 1.], xform='data', button=3, kind='press')
fig.canvas.key_press_event('a') # exit annotation mode
assert_equal(len(raw.annotations.onset), n_anns)
assert_equal(len(raw.annotations.duration), n_anns)
assert_equal(len(raw.annotations.description), n_anns)
plt.close('all')
