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Move evoked topo plot to plot_compare_evokeds

See original GitHub issue

Evoked topoplots should make use of plot_compare_evokeds. I.e., something like this

%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

import mne
from mne.datasets import testing
from mne.channels.layout import _find_topomap_coords
from mne.stats.cluster_level import spatio_temporal_cluster_1samp_test as tst
from mne.defaults import DEFAULTS

data_path = testing.data_path()
fname = data_path + "/EEGLAB/test_raw.set"
montage = data_path + "/EEGLAB/test_chans.locs"

event_id = {"rt":1, "square":2}
eog = {"FPz", "EOG1", "EOG2"}
raw = mne.io.eeglab.read_raw_eeglab(fname, preload=True, eog=eog,
                                    montage=montage, event_id=event_id
                                   )
events = mne.find_events(raw)
picks = mne.pick_types(raw.info, eeg=True)
epochs = mne.Epochs(raw, events,  event_id,
                    tmax=.7, picks=picks)
evoked = epochs["square"].average()

from mne.channels.layout import find_layout
layout = find_layout(evoked.info)
pos = layout.pos.copy()

f = plt.figure()
f.set_size_inches((10, 10))

evokeds = {cond:list(epochs[cond].iter_evoked()) for cond in event_id}
ylims = (evoked.data.min() * DEFAULTS["scalings"]["eeg"],
         evoked.data.max() * DEFAULTS["scalings"]["eeg"])
ylims = (-30, 40)
ymax = np.min(np.abs(np.array(ylims)))
for pick, (pos_, ch_name) in enumerate(zip(pos, evoked.ch_names)):
    ax = plt.axes(pos_)
    mne.viz.plot_compare_evokeds(evokeds, picks=pick, axes=ax,
                         ylim=dict(eeg=ylims),
                         show=False,
                         show_sensors=False,
                        show_legend=False,
                         title='');
    ax.set_xticklabels(())
    ax.set_ylabel('')
    ax.set_xlabel('')
    ax.set_yticks((-ymax, ymax))
    ax.spines["left"].set_bounds(-ymax, ymax)
    ax.set_ylim(ylims)
    ax.set_yticklabels('')
    ax.text(-.1, 1, ch_name, transform=ax.transAxes)

ax_l = plt.axes([0, 0] + list(pos[0, 2:]))
mne.viz.plot_compare_evokeds(evokeds, ylim=dict(eeg=ylims), title='', show_sensors=False,
                     picks=0, axes=ax_l, ci=None,
                             show=False)

ax_l.set_yticks((-ymax, ymax))
ax_l.spines["left"].set_bounds(-ymax, ymax)
ax_l.set_ylim(ylims)
ax_l.lines.clear()
ax_l.patches.clear()