BUG: Fix bug with clip box setting

examples/io/elekta_epochs.py

@@ -5,9 +5,8 @@
 Getting averaging info from .fif files
 ======================================
 
-Parse averaging information defined in Elekta Vectorview/TRIUX DACQ (data
-acquisition). Extract and average epochs accordingly. Modify some
-averaging parameters and get epochs.
+Parse averaging information defined in Elekta Vectorview/TRIUX DACQ (data acquisition).
+Extract and average epochs accordingly. Modify some averaging parameters and get epochs.
 """
 # Author: Jussi Nurminen (jnu@iki.fi)
 #

mne/viz/topo.py

@@ -496,8 +496,6 @@ def _imshow_tfr_unified(
     data_lines.append(
         ax.imshow(
             tfr[ch_idx],
-            clip_on=True,
-            clip_box=tuple(bn.pos),
             extent=extent,
             aspect="auto",
             origin="lower",
@@ -506,6 +504,7 @@ def _imshow_tfr_unified(
             cmap=cmap,
         )
     )
+    data_lines[-1].set_clip_box(_pos_to_bbox(bn.pos, ax))
 
 
 def _plot_timeseries(
@@ -664,18 +663,17 @@ def _plot_timeseries_unified(
     pos = bn.pos
     data_lines = bn.data_lines
     ax = bn.ax
-    # XXX These calls could probably be made faster by using collections
     for data_, color_, times_ in zip(data, color, times):
         data_lines.append(
             ax.plot(
                 bn.x_t + bn.x_s * times_,
                 bn.y_t + bn.y_s * data_[ch_idx],
                 linewidth=0.5,
                 color=color_,
-                clip_on=True,
-                clip_box=tuple(pos),
             )[0]
         )
+        # Needs to be done afterward for some reason (probable matlotlib bug)
+        data_lines[-1].set_clip_box(_pos_to_bbox(pos, ax))
     if vline:
         vline = np.array(vline) * bn.x_s + bn.x_t
         ax.vlines(
@@ -1300,3 +1298,13 @@ def plot_topo_image_epochs(
     add_background_image(fig, fig_background)
     plt_show(show)
     return fig
+
+
+def _pos_to_bbox(pos, ax):
+    """Convert layout position to bbox."""
+    import matplotlib.transforms as mtransforms
+
+    return mtransforms.TransformedBbox(
+        mtransforms.Bbox.from_bounds(*pos),
+        ax.transAxes,
+    )

tutorials/preprocessing/70_fnirs_processing.py

@@ -12,7 +12,6 @@
 
 Here we will work with the :ref:`fNIRS motor data <fnirs-motor-dataset>`.
 """
-
 # %%
 
 import numpy as np

tutorials/time-freq/20_sensors_time_frequency.py

@@ -10,7 +10,7 @@
 
 We will use this dataset: :ref:`somato-dataset`. It contains so-called event
 related synchronizations (ERS) / desynchronizations (ERD) in the beta band.
-"""  # noqa: E501
+"""
 # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
 #          Stefan Appelhoff <stefan.appelhoff@mailbox.org>
 #          Richard Höchenberger <richard.hoechenberger@gmail.com>