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# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: Simplified BSD
import os.path as op
from functools import partial
import numpy as np
from numpy.testing import assert_array_equal, assert_equal
import pytest
from mne import (read_evokeds, read_proj, make_fixed_length_events, Epochs,
compute_proj_evoked, find_layout)
from mne.io.proj import make_eeg_average_ref_proj
from mne.io import read_raw_fif, read_info
from mne.io.constants import FIFF
from mne.io.pick import pick_info, channel_indices_by_type
from mne.io.compensator import get_current_comp
from mne.io.proj import Projection
from mne.channels import read_layout, make_eeg_layout
from mne.datasets import testing
from mne.time_frequency.tfr import AverageTFR
from mne.utils import run_tests_if_main
from mne.viz import plot_evoked_topomap, plot_projs_topomap
from mne.viz.topomap import (_check_outlines, _onselect, plot_topomap,
plot_arrowmap, plot_psds_topomap)
from mne.viz.utils import _find_peaks, _fake_click
# Set our plotters to test mode
import matplotlib
matplotlib.use('Agg') # for testing don't use X server
data_dir = testing.data_path(download=False)
subjects_dir = op.join(data_dir, 'subjects')
ecg_fname = op.join(data_dir, 'MEG', 'sample', 'sample_audvis_ecg-proj.fif')
triux_fname = op.join(data_dir, 'SSS', 'TRIUX', 'triux_bmlhus_erm_raw.fif')
base_dir = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data')
evoked_fname = op.join(base_dir, 'test-ave.fif')
raw_fname = op.join(base_dir, 'test_raw.fif')
event_name = op.join(base_dir, 'test-eve.fif')
ctf_fname = op.join(base_dir, 'test_ctf_comp_raw.fif')
layout = read_layout('Vectorview-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)
@testing.requires_testing_data
def test_plot_projs_topomap():
"""Test plot_projs_topomap."""
import matplotlib.pyplot as plt
projs = read_proj(ecg_fname)
info = read_info(raw_fname)
fast_test = {"res": 8, "contours": 0, "sensors": False}
plot_projs_topomap(projs, info=info, colorbar=True, **fast_test)
plt.close('all')
ax = plt.subplot(111)
projs[3].plot_topomap()
plot_projs_topomap(projs[:1], axes=ax, **fast_test) # test axes param
plt.close('all')
plot_projs_topomap(read_info(triux_fname)['projs'][-1:], **fast_test)
plt.close('all')
plot_projs_topomap(read_info(triux_fname)['projs'][:1], ** fast_test)
plt.close('all')
eeg_avg = make_eeg_average_ref_proj(info)
pytest.raises(RuntimeError, eeg_avg.plot_topomap) # no layout
eeg_avg.plot_topomap(info=info, **fast_test)
plt.close('all')
@pytest.mark.slowtest
@testing.requires_testing_data
def test_plot_topomap():
"""Test topomap plotting."""
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
# evoked
res = 8
fast_test = dict(res=res, contours=0, sensors=False, time_unit='s')
fast_test_noscale = dict(res=res, contours=0, sensors=False)
evoked = read_evokeds(evoked_fname, 'Left Auditory',
baseline=(None, 0))
# Test animation
_, anim = evoked.animate_topomap(ch_type='grad', times=[0, 0.1],
butterfly=False, time_unit='s')
anim._func(1) # _animate has to be tested separately on 'Agg' backend.
plt.close('all')
ev_bad = evoked.copy().pick_types(meg=False, eeg=True)
ev_bad.pick_channels(ev_bad.ch_names[:2])
plt_topomap = partial(ev_bad.plot_topomap, **fast_test)
plt_topomap(times=ev_bad.times[:2] - 1e-6) # auto, plots EEG
pytest.raises(ValueError, plt_topomap, ch_type='mag')
pytest.raises(TypeError, plt_topomap, head_pos='foo')
pytest.raises(KeyError, plt_topomap, head_pos=dict(foo='bar'))
pytest.raises(ValueError, plt_topomap, head_pos=dict(center=0))
pytest.raises(ValueError, plt_topomap, times=[-100]) # bad time
pytest.raises(ValueError, plt_topomap, times=[[0]]) # bad time
evoked.plot_topomap([0.1], ch_type='eeg', scalings=1, res=res,
contours=[-100, 0, 100], time_unit='ms')
plt_topomap = partial(evoked.plot_topomap, **fast_test)
plt_topomap(0.1, layout=layout, scalings=dict(mag=0.1))
plt.close('all')
axes = [plt.subplot(221), plt.subplot(222)]
plt_topomap(axes=axes, colorbar=False)
plt.close('all')
plt_topomap(times=[-0.1, 0.2])
plt.close('all')
evoked_grad = evoked.copy().crop(0, 0).pick_types(meg='grad')
mask = np.zeros((204, 1), bool)
mask[[0, 3, 5, 6]] = True
names = []
def proc_names(x):
names.append(x)
return x[4:]
evoked_grad.plot_topomap(ch_type='grad', times=[0], mask=mask,
show_names=proc_names, **fast_test)
assert_equal(sorted(names),
['MEG 011x', 'MEG 012x', 'MEG 013x', 'MEG 014x'])
mask = np.zeros_like(evoked.data, dtype=bool)
mask[[1, 5], :] = True
plt_topomap(ch_type='mag', outlines=None)
times = [0.1]
plt_topomap(times, ch_type='grad', mask=mask)
plt_topomap(times, ch_type='planar1')
plt_topomap(times, ch_type='planar2')
plt_topomap(times, ch_type='grad', mask=mask, show_names=True,
mask_params={'marker': 'x'})
plt.close('all')
pytest.raises(ValueError, plt_topomap, times, ch_type='eeg', average=-1e3)
pytest.raises(ValueError, plt_topomap, times, ch_type='eeg', average='x')
p = plt_topomap(times, ch_type='grad', image_interp='bilinear',
show_names=lambda x: x.replace('MEG', ''))
subplot = [x for x in p.get_children() if 'Subplot' in str(type(x))]
assert len(subplot) >= 1, [type(x) for x in p.get_children()]
subplot = subplot[0]
assert (all('MEG' not in x.get_text()
for x in subplot.get_children()
if isinstance(x, matplotlib.text.Text)))
# Plot array
for ch_type in ('mag', 'grad'):
evoked_ = evoked.copy().pick_types(eeg=False, meg=ch_type)
plot_topomap(evoked_.data[:, 0], evoked_.info, **fast_test_noscale)
# fail with multiple channel types
pytest.raises(ValueError, plot_topomap, evoked.data[0, :], evoked.info)
# Test title
def get_texts(p):
return [x.get_text() for x in p.get_children() if
isinstance(x, matplotlib.text.Text)]
p = plt_topomap(times, ch_type='eeg', average=0.01)
assert_equal(len(get_texts(p)), 0)
p = plt_topomap(times, ch_type='eeg', title='Custom')
texts = get_texts(p)
assert_equal(len(texts), 1)
assert_equal(texts[0], 'Custom')
plt.close('all')
# delaunay triangulation warning
plt_topomap(times, ch_type='mag', layout=None)
# projs have already been applied
pytest.raises(RuntimeError, plot_evoked_topomap, evoked, 0.1, 'mag',
proj='interactive', time_unit='s')
# change to no-proj mode
evoked = read_evokeds(evoked_fname, 'Left Auditory',
baseline=(None, 0), proj=False)
fig1 = evoked.plot_topomap('interactive', 'mag', proj='interactive',
**fast_test)
_fake_click(fig1, fig1.axes[1], (0.5, 0.5)) # click slider
data_max = np.max(fig1.axes[0].images[0]._A)
fig2 = plt.gcf()
_fake_click(fig2, fig2.axes[0], (0.075, 0.775)) # toggle projector
# make sure projector gets toggled
assert (np.max(fig1.axes[0].images[0]._A) != data_max)
pytest.raises(RuntimeError, plot_evoked_topomap, evoked,
np.repeat(.1, 50), time_unit='s')
pytest.raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6],
time_unit='s')
for ch in evoked.info['chs']:
if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
ch['loc'].fill(0)
# Remove extra digitization point, so EEG digitization points
# correspond with the EEG electrodes
del evoked.info['dig'][85]
pos = make_eeg_layout(evoked.info).pos[:, :2]
pos, outlines = _check_outlines(pos, 'head')
assert ('head' in outlines.keys())
assert ('nose' in outlines.keys())
assert ('ear_left' in outlines.keys())
assert ('ear_right' in outlines.keys())
assert ('autoshrink' in outlines.keys())
assert (outlines['autoshrink'])
assert ('clip_radius' in outlines.keys())
assert_array_equal(outlines['clip_radius'], 0.5)
pos, outlines = _check_outlines(pos, 'skirt')
assert ('head' in outlines.keys())
assert ('nose' in outlines.keys())
assert ('ear_left' in outlines.keys())
assert ('ear_right' in outlines.keys())
assert ('autoshrink' in outlines.keys())
assert (not outlines['autoshrink'])
assert ('clip_radius' in outlines.keys())
assert_array_equal(outlines['clip_radius'], 0.625)
pos, outlines = _check_outlines(pos, 'skirt',
head_pos={'scale': [1.2, 1.2]})
assert_array_equal(outlines['clip_radius'], 0.75)
# Plot skirt
evoked.plot_topomap(times, ch_type='eeg', outlines='skirt', **fast_test)
# Pass custom outlines without patch
evoked.plot_topomap(times, ch_type='eeg', outlines=outlines, **fast_test)
plt.close('all')
# Test interactive cmap
fig = plot_evoked_topomap(evoked, times=[0., 0.1], ch_type='eeg',
cmap=('Reds', True), title='title', **fast_test)
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')
# Pass custom outlines with patch callable
def patch():
return Circle((0.5, 0.4687), radius=.46,
clip_on=True, transform=plt.gca().transAxes)
outlines['patch'] = patch
plot_evoked_topomap(evoked, times, ch_type='eeg', outlines=outlines,
**fast_test)
# Remove digitization points. Now topomap should fail
evoked.info['dig'] = None
pytest.raises(RuntimeError, plot_evoked_topomap, evoked,
times, ch_type='eeg', time_unit='s')
plt.close('all')
# Error for missing names
n_channels = len(pos)
data = np.ones(n_channels)
pytest.raises(ValueError, plot_topomap, data, pos, show_names=True)
# Test error messages for invalid pos parameter
pos_1d = np.zeros(n_channels)
pos_3d = np.zeros((n_channels, 2, 2))
pytest.raises(ValueError, plot_topomap, data, pos_1d)
pytest.raises(ValueError, plot_topomap, data, pos_3d)
pytest.raises(ValueError, plot_topomap, data, pos[:3, :])
pos_x = pos[:, :1]
pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
pytest.raises(ValueError, plot_topomap, data, pos_x)
pytest.raises(ValueError, plot_topomap, data, pos_xyz)
# An #channels x 4 matrix should work though. In this case (x, y, width,
# height) is assumed.
pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
plot_topomap(data, pos_xywh)
plt.close('all')
# Test peak finder
axes = [plt.subplot(131), plt.subplot(132)]
evoked.plot_topomap(times='peaks', axes=axes, **fast_test)
plt.close('all')
evoked.data = np.zeros(evoked.data.shape)
evoked.data[50][1] = 1
assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
evoked.data[80][100] = 1
assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
evoked.data[2][95] = 2
assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])
# Test excluding bads channels
evoked_grad.info['bads'] += [evoked_grad.info['ch_names'][0]]
orig_bads = evoked_grad.info['bads']
evoked_grad.plot_topomap(ch_type='grad', times=[0], time_unit='ms')
assert_array_equal(evoked_grad.info['bads'], orig_bads)
plt.close('all')
def test_plot_tfr_topomap():
"""Test plotting of TFR data."""
import matplotlib as mpl
import matplotlib.pyplot as plt
raw = read_raw_fif(raw_fname)
times = np.linspace(-0.1, 0.1, 200)
res = 8
n_freqs = 3
nave = 1
rng = np.random.RandomState(42)
picks = [93, 94, 96, 97, 21, 22, 24, 25, 129, 130, 315, 316, 2, 5, 8, 11]
info = pick_info(raw.info, picks)
data = rng.randn(len(picks), n_freqs, len(times))
tfr = AverageTFR(info, data, times, np.arange(n_freqs), nave)
tfr.plot_topomap(ch_type='mag', tmin=0.05, tmax=0.150, fmin=0, fmax=10,
res=res, contours=0)
eclick = mpl.backend_bases.MouseEvent('button_press_event',
plt.gcf().canvas, 0, 0, 1)
eclick.xdata = eclick.ydata = 0.1
eclick.inaxes = plt.gca()
erelease = mpl.backend_bases.MouseEvent('button_release_event',
plt.gcf().canvas, 0.9, 0.9, 1)
erelease.xdata = 0.3
erelease.ydata = 0.2
pos = [[0.11, 0.11], [0.25, 0.5], [0.0, 0.2], [0.2, 0.39]]
_onselect(eclick, erelease, tfr, pos, 'grad', 1, 3, 1, 3, 'RdBu_r', list())
_onselect(eclick, erelease, tfr, pos, 'mag', 1, 3, 1, 3, 'RdBu_r', list())
eclick.xdata = eclick.ydata = 0.
erelease.xdata = erelease.ydata = 0.9
tfr._onselect(eclick, erelease, None, 'mean', None)
plt.close('all')
# test plot_psds_topomap
info = raw.info.copy()
chan_inds = channel_indices_by_type(info)
info = pick_info(info, chan_inds['grad'][:4])
fig, axes = plt.subplots()
freqs = np.arange(3., 9.5)
bands = [(4, 8, 'Theta')]
psd = np.random.rand(len(info['ch_names']), freqs.shape[0])
plot_psds_topomap(psd, freqs, info, bands=bands, axes=[axes])
def test_ctf_plotting():
"""Test CTF topomap plotting."""
raw = read_raw_fif(ctf_fname, preload=True)
assert raw.compensation_grade == 3
events = make_fixed_length_events(raw, duration=0.01)
assert len(events) > 10
evoked = Epochs(raw, events, tmin=0, tmax=0.01, baseline=None).average()
assert get_current_comp(evoked.info) == 3
# smoke test that compensation does not matter
evoked.plot_topomap(time_unit='s')
# better test that topomaps can still be used without plotting ref
evoked.pick_types(meg=True, ref_meg=False)
evoked.plot_topomap()
@testing.requires_testing_data
def test_plot_arrowmap():
"""Test arrowmap plotting."""
evoked = read_evokeds(evoked_fname, 'Left Auditory',
baseline=(None, 0))
with pytest.raises(ValueError, match='Multiple channel types'):
plot_arrowmap(evoked.data[:, 0], evoked.info)
evoked_eeg = evoked.copy().pick_types(meg=False, eeg=True)
with pytest.raises(ValueError, match='Multiple channel types'):
plot_arrowmap(evoked_eeg.data[:, 0], evoked.info)
evoked_mag = evoked.copy().pick_types(meg='mag')
evoked_grad = evoked.copy().pick_types(meg='grad')
plot_arrowmap(evoked_mag.data[:, 0], evoked_mag.info)
plot_arrowmap(evoked_grad.data[:, 0], evoked_grad.info,
info_to=evoked_mag.info)
@testing.requires_testing_data
def test_plot_topomap_neuromag122():
"""Test topomap plotting."""
res = 8
fast_test = dict(res=res, contours=0, sensors=False)
evoked = read_evokeds(evoked_fname, 'Left Auditory',
baseline=(None, 0))
evoked.pick_types(meg='grad')
evoked.pick_channels(evoked.ch_names[:122])
ch_names = ['MEG %03d' % k for k in range(1, 123)]
for c in evoked.info['chs']:
c['coil_type'] = FIFF.FIFFV_COIL_NM_122
evoked.rename_channels({c_old: c_new for (c_old, c_new) in
zip(evoked.ch_names, ch_names)})
layout = find_layout(evoked.info)
assert layout.kind.startswith('Neuromag_122')
evoked.plot_topomap(times=[0.1], **fast_test)
proj = Projection(active=False,
desc="test", kind=1,
data=dict(nrow=1, ncol=122,
row_names=None,
col_names=evoked.ch_names, data=np.ones(122)),
explained_var=0.5)
plot_projs_topomap([proj], info=evoked.info, **fast_test)
plot_projs_topomap([proj], layout=layout, **fast_test)
pytest.raises(RuntimeError, plot_projs_topomap, [proj], **fast_test)
run_tests_if_main()
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