MRG, BUG, VIZ: Fix overlay times (mne-tools#8377)

* fix bug

* fstrings

* style

* safer?

* what's new

* touch tutorial to re-render

doc/changes/latest.inc

@@ -27,6 +27,8 @@ Bugs
 ~~~~
 - Fix bug with reading split files that have dashes in the filename **by new contributor** |Eduard Ort|_ (:gh:`8339`)
 
+- Fix bug with `~mne.viz.plot_epochs_image` when ``order`` is supplied and multiple conditions are plotted by `Daniel McCloy`_ (:gh:`8377`)
+
 - Fix bug with :func:`mne.viz.plot_source_estimates` when using the PyVista backend where singleton time points were not handled properly by `Eric Larson`_ (:gh:`8285`)
 
 - Fix bug when passing ``axes`` to plotting functions, :func:`matplotlib.pyplot.tight_layout` will not be called when the figure was created using a constrained layout by `Eric Larson`_ (:gh:`8344`)

examples/visualization/plot_roi_erpimage_by_rt.py

@@ -54,13 +54,13 @@
 # define target events:
 # 1. find response times: distance between "square" and "rt" events
 # 2. extract A. "square" events B. followed by a button press within 700 msec
-tmax = .7
+tmax = 0.7
 sfreq = raw.info["sfreq"]
 reference_id, target_id = 2, 1
 new_events, rts = define_target_events(events, reference_id, target_id, sfreq,
                                        tmin=0., tmax=tmax, new_id=2)
 
-epochs = mne.Epochs(raw, events=new_events, tmax=tmax + .1,
+epochs = mne.Epochs(raw, events=new_events, tmax=tmax + 0.1,
                     event_id={"square": 2})
 
 ###############################################################################

mne/viz/epochs.py

@@ -289,8 +289,8 @@ def plot_epochs_image(epochs, picks=None, sigma=0., vmin=None,
         this_image = combine_func(this_data * scalings[this_ch_type])
         # handle `order`. NB: this can potentially yield different orderings
         # in each figure!
-        this_image, overlay_times = _order_epochs(this_image, epochs.times,
-                                                  order, overlay_times)
+        this_image, _overlay_times = _order_epochs(this_image, epochs.times,
+                                                   order, overlay_times)
         this_norm = np.all(this_image > 0)
         # apply smoothing
         if sigma > 0.:
@@ -325,7 +325,7 @@ def plot_epochs_image(epochs, picks=None, sigma=0., vmin=None,
             if isinstance(combine, str) and len(title):
                 _comb = combine.upper() if combine == 'gfp' else combine
                 _comb = 'std. dev.' if _comb == 'std' else _comb
-                title += ' ({})'.format(_comb)
+                title += f' ({_comb})'
 
         # plot the image
         this_fig = _plot_epochs_image(
@@ -334,7 +334,7 @@ def plot_epochs_image(epochs, picks=None, sigma=0., vmin=None,
             style_axes=True, norm=this_group_dict['norm'],
             unit=units[this_ch_type], ax=this_axes_dict, show=False,
             title=title, combine=combine, combine_given=combine_given,
-            overlay_times=overlay_times, evoked=evoked, ts_args=ts_args)
+            overlay_times=_overlay_times, evoked=evoked, ts_args=ts_args)
         group_by[this_group].update(fig=this_fig)
 
         # detect ylims across figures
@@ -478,27 +478,25 @@ def _order_epochs(data, times, order=None, overlay_times=None):
 
     if overlay_times is not None:
         if len(overlay_times) != n_epochs:
-            raise ValueError('size of overlay_times parameter ({}) does not '
-                             'match the number of epochs ({}).'
-                             .format(len(overlay_times), n_epochs))
+            raise ValueError(
+                f'size of overlay_times parameter ({len(overlay_times)}) does '
+                f'not match the number of epochs ({n_epochs}).')
         overlay_times = np.array(overlay_times)
         times_min = np.min(overlay_times)
         times_max = np.max(overlay_times)
-        if ((times_min < times[0]) or (times_max > times[-1])):
+        if (times_min < times[0]) or (times_max > times[-1]):
             warn('Some values in overlay_times fall outside of the epochs '
-                 'time interval (between %s s and %s s)'
-                 % (times[0], times[-1]))
+                 f'time interval (between {times[0]} s and {times[-1]} s)')
 
     if callable(order):
         order = order(times, data)
 
     if order is not None:
         if len(order) != n_epochs:
-            raise ValueError('If order is a {}, its length ({}) must match '
-                             'the length of the data ({}).'
-                             .format(type(order).__name__, len(order),
-                                     n_epochs))
-        order = np.asarray(order)
+            raise ValueError(f'If order is a {type(order).__name__}, its '
+                             f'length ({len(order)}) must match the length of '
+                             f'the data ({n_epochs}).')
+        order = np.array(order)
         data = data[order]
         if overlay_times is not None:
             overlay_times = overlay_times[order]