matplotlib
diff --git a/‎examples/animation/animated_histogram.py
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diff --git a/‎examples/animation/multiple_axes.py
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diff --git a/‎examples/axes_grid1/demo_axes_hbox_divider.py
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diff --git a/‎examples/axes_grid1/demo_fixed_size_axes.py
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diff --git a/‎examples/axes_grid1/inset_locator_demo.py
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diff --git a/‎examples/axes_grid1/make_room_for_ylabel_using_axesgrid.py
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diff --git a/‎examples/axes_grid1/scatter_hist_locatable_axes.py
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diff --git a/‎examples/axes_grid1/simple_axes_divider1.py
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diff --git a/‎examples/axisartist/demo_floating_axes.py
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diff --git a/‎examples/color/color_by_yvalue.py
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diff --git a/‎examples/color/color_cycle_default.py
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diff --git a/‎examples/color/color_demo.py
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diff --git a/‎examples/color/colorbar_basics.py
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diff --git a/‎examples/color/colormap_reference.py
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diff --git a/‎examples/color/custom_cmap.py
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diff --git a/‎examples/color/named_colors.py
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diff --git a/‎examples/event_handling/cursor_demo.py
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diff --git a/‎examples/event_handling/ginput_manual_clabel_sgskip.py
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diff --git a/‎examples/event_handling/pick_event_demo.py
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diff --git a/‎examples/images_contours_and_fields/affine_image.py
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diff --git a/‎examples/images_contours_and_fields/barb_demo.py
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diff --git a/‎examples/images_contours_and_fields/barcode_demo.py
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@@ -21,7 +21,7 @@
 data = np.random.randn(1000)
 n, _ = np.histogram(data, HIST_BINS)
 
-###############################################################################
+# %%
 # To animate the histogram, we need an ``animate`` function, which generates
 # a random set of numbers and updates the heights of rectangles. We utilize a
 # python closure to track an instance of `.BarContainer` whose `.Rectangle`
@@ -39,7 +39,7 @@ def animate(frame_number):
         return bar_container.patches
     return animate
 
-###############################################################################
+# %%
 # Using :func:`~matplotlib.pyplot.hist` allows us to get an instance of
 # `.BarContainer`, which is a collection of `.Rectangle` instances. Calling
 # ``prepare_animation`` will define ``animate`` function working with supplied
 
@@ -70,7 +70,7 @@ def animate(i):
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -33,7 +33,7 @@
 
 plt.show()
 
-###############################################################################
+# %%
 # Using a `.VBoxDivider` to arrange subplots.
 #
 # Note that both axes' location are adjusted so that they have
 
@@ -8,7 +8,7 @@
 
 from mpl_toolkits.axes_grid1 import Divider, Size
 
-###############################################################################
+# %%
 
 
 fig = plt.figure(figsize=(6, 6))
@@ -26,7 +26,7 @@
 
 ax.plot([1, 2, 3])
 
-###############################################################################
+# %%
 
 
 fig = plt.figure(figsize=(6, 6))
 
@@ -5,7 +5,7 @@
 
 """
 
-###############################################################################
+# %%
 # The `.inset_locator`'s `~.inset_locator.inset_axes` allows
 # easily placing insets in the corners of the axes by specifying a width and
 # height and optionally a location (loc) that accepts locations as codes,
@@ -43,7 +43,7 @@
 plt.show()
 
 
-###############################################################################
+# %%
 # The parameters *bbox_to_anchor* and *bbox_transform* can be used for a more
 # fine-grained control over the inset position and size or even to position
 # the inset at completely arbitrary positions.
@@ -100,7 +100,7 @@
 plt.show()
 
 
-###############################################################################
+# %%
 # In the above the axes transform together with 4-tuple bounding boxes has been
 # used as it mostly is useful to specify an inset relative to the axes it is
 # an inset to. However, other use cases are equally possible. The following
 
@@ -17,7 +17,7 @@
 
 make_axes_area_auto_adjustable(ax)
 
-###############################################################################
+# %%
 
 fig = plt.figure()
 ax1 = fig.add_axes([0, 0, 1, 0.5])
@@ -31,7 +31,7 @@
 make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
 make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
 
-###############################################################################
+# %%
 
 fig = plt.figure()
 ax1 = fig.add_axes([0, 0, 1, 1])
 
@@ -63,7 +63,7 @@
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -18,7 +18,7 @@ def label_axes(ax, text):
                    left=False, labelleft=False)
 
 
-##############################################################################
+# %%
 # Fixed axes sizes; fixed paddings.
 
 fig = plt.figure(figsize=(6, 6))
@@ -42,7 +42,7 @@ def label_axes(ax, text):
 ax4 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, nx1=4, ny=0))
 label_axes(ax4, "nx=2, nx1=4, ny=0")
 
-##############################################################################
+# %%
 # Axes sizes that scale with the figure size; fixed paddings.
 
 fig = plt.figure(figsize=(6, 6))
 
@@ -145,7 +145,7 @@ def setup_axes3(fig, rect):
     return ax1, aux_ax
 
 
-##########################################################
+# %%
 fig = plt.figure(figsize=(8, 4))
 fig.subplots_adjust(wspace=0.3, left=0.05, right=0.95)
 
 
@@ -22,7 +22,7 @@
 ax.plot(t, smiddle, t, slower, t, supper)
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -40,7 +40,7 @@
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -61,7 +61,7 @@
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -45,7 +45,7 @@
 cbar.minorticks_on()
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -68,7 +68,7 @@ def plot_color_gradients(cmap_category, cmap_list):
     plot_color_gradients(cmap_category, cmap_list)
 
 
-###############################################################################
+# %%
 # .. _reverse-cmap:
 #
 # Reversed colormaps
@@ -83,7 +83,7 @@ def plot_color_gradients(cmap_category, cmap_list):
 # The built-in reversed colormaps are generated using `.Colormap.reversed`.
 # For an example, see :ref:`reversing-colormap`
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -108,7 +108,7 @@
 Z = np.cos(X) * np.sin(Y) * 10
 
 
-###############################################################################
+# %%
 # Colormaps from a list
 # ---------------------
 
@@ -126,7 +126,7 @@
     fig.colorbar(im, ax=ax)
 
 
-###############################################################################
+# %%
 # Custom colormaps
 # ----------------
 
@@ -202,14 +202,14 @@
 }
 
 
-###############################################################################
+# %%
 # Now we will use this example to illustrate 2 ways of
 # handling custom colormaps.
 # First, the most direct and explicit:
 
 blue_red1 = LinearSegmentedColormap('BlueRed1', cdict1)
 
-###############################################################################
+# %%
 # Second, create the map explicitly and register it.
 # Like the first method, this method works with any kind
 # of Colormap, not just
@@ -219,7 +219,7 @@
 mpl.colormaps.register(LinearSegmentedColormap('BlueRed3', cdict3))
 mpl.colormaps.register(LinearSegmentedColormap('BlueRedAlpha', cdict4))
 
-###############################################################################
+# %%
 # Make the figure, with 4 subplots:
 
 fig, axs = plt.subplots(2, 2, figsize=(6, 9))
@@ -264,7 +264,7 @@
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -73,21 +73,21 @@ def plot_colortable(colors, *, ncols=4, sort_colors=True):
 
     return fig
 
-#############################################################################
+# %%
 # -----------
 # Base colors
 # -----------
 
 plot_colortable(mcolors.BASE_COLORS, ncols=3, sort_colors=False)
 
-#############################################################################
+# %%
 # ---------------
 # Tableau Palette
 # ---------------
 
 plot_colortable(mcolors.TABLEAU_COLORS, ncols=2, sort_colors=False)
 
-#############################################################################
+# %%
 # ----------
 # CSS Colors
 # ----------
@@ -96,7 +96,7 @@ def plot_colortable(colors, *, ncols=4, sort_colors=True):
 plot_colortable(mcolors.CSS4_COLORS)
 plt.show()
 
-#############################################################################
+# %%
 # -----------
 # XKCD Colors
 # -----------
 
@@ -72,7 +72,7 @@ def on_mouse_move(self, event):
 fig.canvas.mpl_connect('motion_notify_event', cursor.on_mouse_move)
 
 
-##############################################################################
+# %%
 # Faster redrawing using blitting
 # """""""""""""""""""""""""""""""
 # This technique stores the rendered plot as a background image. Only the
@@ -153,7 +153,7 @@ def on_mouse_move(self, event):
 fig.canvas.mpl_connect('motion_notify_event', blitted_cursor.on_mouse_move)
 
 
-##############################################################################
+# %%
 # Snapping to data points
 # """""""""""""""""""""""
 # The following cursor snaps its position to the data points of a `.Line2D`
 
@@ -26,7 +26,7 @@ def tellme(s):
     plt.title(s, fontsize=16)
     plt.draw()
 
-##################################################
+# %%
 # Define a triangle by clicking three points
 
 
@@ -59,7 +59,7 @@ def tellme(s):
         p.remove()
 
 
-##################################################
+# %%
 # Now contour according to distance from triangle
 # corners - just an example
 
@@ -79,7 +79,7 @@ def f(x, y, pts):
 tellme('Use mouse to select contour label locations, middle button to finish')
 CL = plt.clabel(CS, manual=True)
 
-##################################################
+# %%
 # Now do a zoom
 
 tellme('Now do a nested zoom, click to begin')
 
@@ -84,7 +84,7 @@ def pick_handler(event):
 np.random.seed(19680801)
 
 
-#############################################################################
+# %%
 # Simple picking, lines, rectangles and text
 # ------------------------------------------
 
@@ -117,7 +117,7 @@ def onpick1(event):
 fig.canvas.mpl_connect('pick_event', onpick1)
 
 
-#############################################################################
+# %%
 # Picking with a custom hit test function
 # ---------------------------------------
 # You can define custom pickers by setting picker to a callable function. The
@@ -163,7 +163,7 @@ def onpick2(event):
 fig.canvas.mpl_connect('pick_event', onpick2)
 
 
-#############################################################################
+# %%
 # Picking on a scatter plot
 # -------------------------
 # A scatter plot is backed by a `~matplotlib.collections.PathCollection`.
@@ -181,7 +181,7 @@ def onpick3(event):
 fig.canvas.mpl_connect('pick_event', onpick3)
 
 
-#############################################################################
+# %%
 # Picking images
 # --------------
 # Images plotted using `.Axes.imshow` are `~matplotlib.image.AxesImage`
 
@@ -64,7 +64,7 @@ def do_plot(ax, Z, transform):
 plt.show()
 
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -47,15 +47,15 @@
 masked_u[4] = 1000  # Bad value that should not be plotted when masked
 masked_u[4] = np.ma.masked
 
-#############################################################################
+# %%
 # Identical plot to panel 2 in the first figure, but with the point at
 # (0.5, 0.25) missing (masked)
 fig2, ax2 = plt.subplots()
 ax2.barbs(data['x'], data['y'], masked_u, data['v'], length=8, pivot='middle')
 
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
 
@@ -37,7 +37,7 @@
           interpolation='nearest')
 plt.show()
 
-#############################################################################
+# %%
 #
 # .. admonition:: References
 #
Original file line number	Diff line number	Diff line change
`@@ -70,7 +70,7 @@ def animate(i):`
`70`	`70`
`71`	`71`	`plt.show()`
`72`	`72`
`73`		`-#############################################################################`
	`73`	`+# %%`
`74`	`74`	`#`
`75`	`75`	`# .. admonition:: References`
`76`	`76`	`#`
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`@@ -33,7 +33,7 @@`
`33`	`33`
`34`	`34`	`plt.show()`
`35`	`35`
`36`		`-###############################################################################`
	`36`	`+# %%`
`37`	`37`	# Using a `.VBoxDivider` to arrange subplots.
`38`	`38`	`#`
`39`	`39`	`# Note that both axes' location are adjusted so that they have`
Original file line number	Diff line number	Diff line change
`@@ -63,7 +63,7 @@`
`63`	`63`
`64`	`64`	`plt.show()`
`65`	`65`
`66`		`-#############################################################################`
	`66`	`+# %%`
`67`	`67`	`#`
`68`	`68`	`# .. admonition:: References`
`69`	`69`	`#`
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`@@ -22,7 +22,7 @@`
`22`	`22`	`ax.plot(t, smiddle, t, slower, t, supper)`
`23`	`23`	`plt.show()`
`24`	`24`
`25`		`-#############################################################################`
	`25`	`+# %%`
`26`	`26`	`#`
`27`	`27`	`# .. admonition:: References`
`28`	`28`	`#`
Original file line number	Diff line number	Diff line change
`@@ -40,7 +40,7 @@`
`40`	`40`
`41`	`41`	`plt.show()`
`42`	`42`
`43`		`-#############################################################################`
	`43`	`+# %%`
`44`	`44`	`#`
`45`	`45`	`# .. admonition:: References`
`46`	`46`	`#`
Original file line number	Diff line number	Diff line change
`@@ -61,7 +61,7 @@`
`61`	`61`
`62`	`62`	`plt.show()`
`63`	`63`
`64`		`-#############################################################################`
	`64`	`+# %%`
`65`	`65`	`#`
`66`	`66`	`# .. admonition:: References`
`67`	`67`	`#`
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`@@ -45,7 +45,7 @@`
`45`	`45`	`cbar.minorticks_on()`
`46`	`46`	`plt.show()`
`47`	`47`
`48`		`-#############################################################################`
	`48`	`+# %%`
`49`	`49`	`#`
`50`	`50`	`# .. admonition:: References`
`51`	`51`	`#`
Original file line number	Diff line number	Diff line change
`@@ -68,7 +68,7 @@ def plot_color_gradients(cmap_category, cmap_list):`
`68`	`68`	`plot_color_gradients(cmap_category, cmap_list)`
`69`	`69`
`70`	`70`
`71`		`-###############################################################################`
	`71`	`+# %%`
`72`	`72`	`# .. _reverse-cmap:`
`73`	`73`	`#`
`74`	`74`	`# Reversed colormaps`
`@@ -83,7 +83,7 @@ def plot_color_gradients(cmap_category, cmap_list):`
`83`	`83`	# The built-in reversed colormaps are generated using `.Colormap.reversed`.
`84`	`84`	# For an example, see :ref:`reversing-colormap`
`85`	`85`
`86`		`-#############################################################################`
	`86`	`+# %%`
`87`	`87`	`#`
`88`	`88`	`# .. admonition:: References`
`89`	`89`	`#`
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`@@ -64,7 +64,7 @@ def do_plot(ax, Z, transform):`
`64`	`64`	`plt.show()`
`65`	`65`
`66`	`66`
`67`		`-#############################################################################`
	`67`	`+# %%`
`68`	`68`	`#`
`69`	`69`	`# .. admonition:: References`
`70`	`70`	`#`
Original file line number	Diff line number	Diff line change
`@@ -37,7 +37,7 @@`
`37`	`37`	`interpolation='nearest')`
`38`	`38`	`plt.show()`
`39`	`39`
`40`		`-#############################################################################`
	`40`	`+# %%`
`41`	`41`	`#`
`42`	`42`	`# .. admonition:: References`
`43`	`43`	`#`