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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import numpy as np
import pytest
from mne import compute_proj_evoked, pick_types, read_evokeds
from mne.datasets import testing
from mne.viz import plot_projs_joint
data_dir = testing.data_path(download=False)
sample_dir = data_dir / "MEG" / "sample"
evoked_fname = sample_dir / "sample_audvis-ave.fif"
@testing.requires_testing_data
def test_plot_projs_joint():
"""Test plot_projs_joint."""
evoked = read_evokeds(evoked_fname)[0].apply_baseline((None, 0))
evoked.info["bads"] = []
n_mag, n_grad, n_eeg = 9, 10, 11
n_mag_proj, n_grad_proj, n_eeg_proj = 2, 2, 1
# We pick in this weird order to ensure our plotting order follows it
picks = np.concatenate(
[
pick_types(evoked.info, meg="grad")[:n_grad],
pick_types(evoked.info, meg=False, eeg=True)[:n_eeg],
pick_types(evoked.info, meg="mag")[:n_mag],
]
)
evoked.pick(picks)
assert len(evoked.ch_names) == n_mag + n_grad + n_eeg
assert evoked.get_channel_types(unique=True) == ["grad", "eeg", "mag"]
projs = compute_proj_evoked(
evoked, n_mag=n_mag_proj, n_grad=n_grad_proj, n_eeg=n_eeg_proj
)
assert len(projs) == 5
with pytest.warns(RuntimeWarning, match="aliasing"):
evoked.crop(-0.1, 0.1).decimate(10)
topomap_kwargs = dict(res=8, contours=0, sensors=False)
fig = plot_projs_joint(
projs, evoked, topomap_kwargs=topomap_kwargs, verbose="error"
)
ylab = fig.axes[0].get_ylabel()
assert ylab.startswith("Grad"), ylab
ylab = fig.axes[4].get_ylabel()
assert ylab.startswith("EEG"), ylab
ylab = fig.axes[7].get_ylabel()
assert ylab.startswith("Mag"), ylab
mag_trace_ax_idx = 10
mag_trace_ax = fig.axes[mag_trace_ax_idx]
assert mag_trace_ax.get_ylabel() == ""
assert len(mag_trace_ax.lines) == n_mag + 2 * n_mag_proj
old_len = len(mag_trace_ax.lines)
assert len(fig.axes) == 11 # 3x4
fig = plot_projs_joint(
projs,
evoked,
picks_trace="MEG 0111",
topomap_kwargs=topomap_kwargs,
verbose="error",
)
assert len(fig.axes[mag_trace_ax_idx].lines) == old_len + 1
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