MAINT: Fix CircleCI [circle deploy] (mne-tools#13089)

Author: larsoner

mne/viz/utils.py

@@ -1185,7 +1185,7 @@ def _onpick_sensor(event, fig, ax, pos, ch_names, show_names):
     fig.canvas.draw()
 
 
-def _close_event(event, fig):
+def _close_event(event=None, fig=None):
     """Listen for sensor plotter close event."""
     if getattr(fig, "lasso", None) is not None:
         fig.lasso.disconnect()

tutorials/epochs/60_make_fixed_length_epochs.py

@@ -5,11 +5,10 @@
 =================================================
 
 This tutorial shows how to segment continuous data into a set of epochs spaced
-equidistantly in time. The epochs will not be created based on experimental
-events; instead, the continuous data will be "chunked" into consecutive epochs
-(which may be temporally overlapping, adjacent, or separated).
-We will also briefly demonstrate how to use these epochs in connectivity
-analysis.
+equidistantly in time. The epochs will not be created based on experimental events;
+instead, the continuous data will be "chunked" into consecutive epochs (which may be
+temporally overlapping, adjacent, or separated). We will also briefly demonstrate how
+to use these epochs in connectivity analysis.
 
 First, we import the necessary modules and read in a sample raw data set.
 This data set contains brain activity that is event-related, i.e.,

tutorials/evoked/10_evoked_overview.py

@@ -5,12 +5,11 @@
 The Evoked data structure: evoked/averaged data
 ===============================================
 
-This tutorial covers the basics of creating and working with :term:`evoked`
-data. It introduces the :class:`~mne.Evoked` data structure in detail,
-including how to load, query, subset, export, and plot data from an
-:class:`~mne.Evoked` object. For details on creating an :class:`~mne.Evoked`
-object from (possibly simulated) data in a :class:`NumPy array
-<numpy.ndarray>`, see :ref:`tut-creating-data-structures`.
+This tutorial covers the basics of creating and working with :term:`evoked` data. It
+introduces the :class:`~mne.Evoked` data structure in detail, including how to load,
+query, subset, export, and plot data from an :class:`~mne.Evoked` object. For details
+on creating an :class:`~mne.Evoked` object from (possibly simulated) data in a
+:class:`NumPy array <numpy.ndarray>`, see :ref:`tut-creating-data-structures`.
 
 As usual, we start by importing the modules we need:
 """