def test_plot():
"""Test TFR plotting."""
import matplotlib
matplotlib.use('Agg') # for testing don't use X server
import matplotlib.pyplot as plt
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')
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_topo()
plt.close('all')
def test_plot_tfr_topo():
"""Test plotting of TFR data."""
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 (at least 2.0) 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_tfr_topo():
"""Test plotting of TFR data."""
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)
tfr.plot_topo(baseline=(None, 0), mode='ratio', title='Average power',
vmin=0., vmax=14., show=False)
tfr.plot([4], baseline=(None, 0), mode='ratio', show=False, title='foo')
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)
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())
_fake_click(fig, fig.axes[-1], (0.08, 0.65))
assert_equal(num_figures_before + 1, len(plt.get_fignums()))
plt.close('all')
tfr.plot([4], baseline=(None, 0), mode='ratio', show=False, title='foo')
assert_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_equal(fig.axes[0].get_yaxis().get_scale(), 'log')
# one timesample
tfr = AverageTFR(epochs.info, data[:, :, [0]], epochs.times[[1]],
freqs, nave)
tfr.plot([4], baseline=None, vmax=14., show=False, yscale='linear')
# one freqency 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]
_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_equal(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
assert_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():
"""Test TFR plotting."""
import matplotlib.pyplot as plt
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)
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_topo(picks=[1, 2])
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():
"""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')
# test title=auto, combine=None, and correct length of figure list
picks = [1, 2]
figs = tfr.plot(picks,
title='auto',
colorbar=False,
mask=np.ones(tfr.data.shape[1:], bool))
assert len(figs) == len(picks)
assert 'MEG' in figs[0].texts[0].get_text()
plt.close('all')
# test combine and title keyword
figs = tfr.plot(picks,
title='title',
colorbar=False,
combine='rms',
mask=np.ones(tfr.data.shape[1:], bool))
assert len(figs) == 1
assert figs[0].texts[0].get_text() == 'title'
figs = tfr.plot(picks,
title='auto',
colorbar=False,
combine='mean',
mask=np.ones(tfr.data.shape[1:], bool))
assert len(figs) == 1
assert figs[0].texts[0].get_text() == 'Mean of 2 sensors'
with pytest.raises(ValueError, match='combine must be None'):
tfr.plot(picks,
colorbar=False,
combine='something',
mask=np.ones(tfr.data.shape[1:], bool))
plt.close('all')
# test axes argument - first with list of axes
ax = plt.subplot2grid((2, 2), (0, 0))
ax2 = plt.subplot2grid((2, 2), (0, 1))
ax3 = plt.subplot2grid((2, 2), (1, 0))
figs = tfr.plot(picks=[0, 1, 2], axes=[ax, ax2, ax3])
assert len(figs) == len([ax, ax2, ax3])
# and as a single axes
figs = tfr.plot(picks=[0], axes=ax)
assert len(figs) == 1
plt.close('all')
# and invalid inputs
with pytest.raises(ValueError, match='axes must be None'):
tfr.plot(picks,
colorbar=False,
axes={},
mask=np.ones(tfr.data.shape[1:], bool))
# different number of axes and picks should throw a RuntimeError
with pytest.raises(RuntimeError, match='There must be an axes'):
tfr.plot(picks=[0],
colorbar=False,
axes=[ax, ax2],
mask=np.ones(tfr.data.shape[1:], bool))
tfr.plot_topo(picks=[1, 2])
plt.close('all')
# interactive mode on by default
fig = tfr.plot(picks=[1], cmap='RdBu_r')[0]
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')