Fix issue where set ylim parameter gets swapped across channel types in plot_evoked_topo

doc/changes/latest.inc

@@ -173,6 +173,8 @@ Enhancements
 
 Bugs
 ~~~~
+- Fix bug with :func:`mne.viz.plot_evoked_topo` where set ylim parameters gets swapped across channel types. (:gh:`9207` by |Ram Pari|_)
+
 - Fix bug with :func:`mne.io.read_raw_edf` where µV was not correctly recognized (:gh:`9187` **by new contributor** |Sumalyo Datta|_)
 
 - Fix bug with :func:`mne.viz.plot_compare_evokeds` did not check type of combine. (:gh:`9151` **by new contributor** |Matteo Anelli|_)

mne/viz/topo.py

@@ -230,16 +230,9 @@ def _plot_topo(info, times, show_func, click_func=None, layout=None,
                                     fig_facecolor=fig_facecolor,
                                     unified=unified, img=img, axes=axes)
 
-    # Temporarily converting the ylim to a list to avoid zip object exhaustion
-    if ylim is not None:
-        ylim_list = [list(t) for t in zip(*ylim)]
-    else:
-        ylim_list = ylim
-
     for ax, ch_idx in my_topo_plot:
-        if layout.kind == 'Vectorview-all' and ylim_list is not None:
+        if layout.kind == 'Vectorview-all' and ylim is not None:
             this_type = {'mag': 0, 'grad': 1}[channel_type(info, ch_idx)]
-            ylim = zip(*ylim_list)
             ylim_ = [v[this_type] if _check_vlim(v) else v for v in ylim]
         else:
             ylim_ = ylim
@@ -713,16 +706,19 @@ def _plot_evoked_topo(evoked, layout=None, layout_scale=0.945, color=None,
 
     if not merge_channels:
         # XXX. at the moment we are committed to 1- / 2-sensor-types layouts
-        chs_in_layout = set(layout.names) & set(ch_names)
-        types_used = {channel_type(info, ch_names.index(ch))
-                      for ch in chs_in_layout}
+        chs_in_layout = [ch_name for ch_name in ch_names
+                         if ch_name in layout.names]
+        types_used = [channel_type(info, ch_names.index(ch))
+                      for ch in chs_in_layout]
+        # Using dict conversion to remove duplicates
+        types_used = list(dict.fromkeys(types_used))
         # remove possible reference meg channels
-        types_used = set.difference(types_used, set('ref_meg'))
+        types_used = [types_used for types_used in types_used
+                      if types_used != 'ref_meg']
         # one check for all vendors
-        meg_types = {'mag', 'grad'}
-        is_meg = len(set.intersection(types_used, meg_types)) > 0
-        nirs_types = {'hbo', 'hbr', 'fnirs_cw_amplitude', 'fnirs_od'}
-        is_nirs = len(set.intersection(types_used, nirs_types)) > 0
+        is_meg = len([x for x in types_used if x in ['mag', 'grad']]) > 0
+        is_nirs = len([x for x in types_used if x in
+                      ('hbo', 'hbr', 'fnirs_cw_amplitude', 'fnirs_od')]) > 0
         if is_meg:
             types_used = list(types_used)[::-1]  # -> restore kwarg order
             picks = [pick_types(info, meg=kk, ref_meg=False, exclude=[])
@@ -768,7 +764,10 @@ def _plot_evoked_topo(evoked, layout=None, layout_scale=0.945, color=None,
         if len(ylim_) == 1:
             ylim_ = ylim_[0]
         else:
-            ylim_ = zip(*[np.array(yl) for yl in ylim_])
+            ylim_ = [np.array(yl) for yl in ylim_]
+            # Transposing to avoid Zipping confusion
+            if is_meg or is_nirs:
+                ylim_ = list(map(list, zip(*ylim_)))
     else:
         raise TypeError('ylim must be None or a dict. Got %s.' % type(ylim))