diff --git a/lib/matplotlib/_constrained_layout.py b/lib/matplotlib/_constrained_layout.py
index ab156217b859..c6e0e7dc05b8 100644
--- a/lib/matplotlib/_constrained_layout.py
+++ b/lib/matplotlib/_constrained_layout.py
@@ -99,44 +99,42 @@ def do_constrained_layout(fig, renderer, h_pad, w_pad,
 
     """
 
-    '''  Steps:
-
-    1. get a list of unique gridspecs in this figure.  Each gridspec will be
-    constrained separately.
-    2. Check for gaps in the gridspecs.  i.e. if not every axes slot in the
-    gridspec has been filled.  If empty, add a ghost axis that is made so
-    that it cannot be seen (though visible=True).  This is needed to make
-    a blank spot in the layout.
-    3. Compare the tight_bbox of each axes to its `position`, and assume that
-    the difference is the space needed by the elements around the edge of
-    the axes (decorations) like the title, ticklabels, x-labels, etc.  This
-    can include legends who overspill the axes boundaries.
-    4. Constrain gridspec elements to line up:
-        a) if colnum0 != colnumC, the two subplotspecs are stacked next to
-        each other, with the appropriate order.
-        b) if colnum0 == colnumC, line up the left or right side of the
-        _poslayoutbox (depending if it is the min or max num that is equal).
-        c) do the same for rows...
-    5. The above doesn't constrain relative sizes of the _poslayoutboxes at
-    all, and indeed zero-size is a solution that the solver often finds more
-    convenient than expanding the sizes.  Right now the solution is to compare
-    subplotspec sizes (i.e. drowsC and drows0) and constrain the larger
-    _poslayoutbox to be larger than the ratio of the sizes.  i.e. if drows0 >
-    drowsC,  then ax._poslayoutbox > axc._poslayoutbox * drowsC / drows0. This
-    works fine *if* the decorations are similar between the axes.  If the
-    larger subplotspec has much larger axes decorations, then the constraint
-    above is incorrect.
-
-    We need the greater than in the above, in general, rather than an equals
-    sign.  Consider the case of the left column having 2 rows, and the right
-    column having 1 row.  We want the top and bottom of the _poslayoutboxes to
-    line up. So that means if there are decorations on the left column axes
-    they will be smaller than half as large as the right hand axis.
-
-    This can break down if the decoration size for the right hand axis (the
-    margins) is very large.  There must be a math way to check for this case.
-
-    '''
+    # Steps:
+    #
+    # 1. get a list of unique gridspecs in this figure.  Each gridspec will be
+    # constrained separately.
+    # 2. Check for gaps in the gridspecs.  i.e. if not every axes slot in the
+    # gridspec has been filled.  If empty, add a ghost axis that is made so
+    # that it cannot be seen (though visible=True).  This is needed to make
+    # a blank spot in the layout.
+    # 3. Compare the tight_bbox of each axes to its `position`, and assume that
+    # the difference is the space needed by the elements around the edge of
+    # the axes (decorations) like the title, ticklabels, x-labels, etc.  This
+    # can include legends who overspill the axes boundaries.
+    # 4. Constrain gridspec elements to line up:
+    #     a) if colnum0 != colnumC, the two subplotspecs are stacked next to
+    #     each other, with the appropriate order.
+    #     b) if colnum0 == colnumC, line up the left or right side of the
+    #     _poslayoutbox (depending if it is the min or max num that is equal).
+    #     c) do the same for rows...
+    # 5. The above doesn't constrain relative sizes of the _poslayoutboxes
+    # at all, and indeed zero-size is a solution that the solver often finds
+    # more convenient than expanding the sizes.  Right now the solution is to
+    # compare subplotspec sizes (i.e. drowsC and drows0) and constrain the
+    # larger _poslayoutbox to be larger than the ratio of the sizes. i.e. if
+    # drows0 > drowsC, then ax._poslayoutbox > axc._poslayoutbox*drowsC/drows0.
+    # This works fine *if* the decorations are similar between the axes.
+    # If the larger subplotspec has much larger axes decorations, then the
+    # constraint above is incorrect.
+    #
+    # We need the greater than in the above, in general, rather than an equals
+    # sign.  Consider the case of the left column having 2 rows, and the right
+    # column having 1 row.  We want the top and bottom of the _poslayoutboxes
+    # to line up. So that means if there are decorations on the left column
+    # axes they will be smaller than half as large as the right hand axis.
+    #
+    # This can break down if the decoration size for the right hand axis (the
+    # margins) is very large.  There must be a math way to check for this case.
 
     invTransFig = fig.transFigure.inverted().transform_bbox
 
diff --git a/lib/matplotlib/_layoutbox.py b/lib/matplotlib/_layoutbox.py
index 4f31f7bdb95e..bca14d74e947 100644
--- a/lib/matplotlib/_layoutbox.py
+++ b/lib/matplotlib/_layoutbox.py
@@ -623,29 +623,21 @@ def match_margins(boxes, levels=1):
 
 
 def seq_id():
-    '''
-    Generate a short sequential id for layoutbox objects...
-    '''
-
-    global _layoutboxobjnum
-
-    return ('%06d' % (next(_layoutboxobjnum)))
+    """Generate a short sequential id for layoutbox objects."""
+    return '%06d' % next(_layoutboxobjnum)
 
 
 def print_children(lb):
-    '''
-    Print the children of the layoutbox
-    '''
+    """Print the children of the layoutbox."""
     print(lb)
     for child in lb.children:
         print_children(child)
 
 
 def nonetree(lb):
-    '''
-    Make all elements in this tree none...  This signals not to do any more
-    layout.
-    '''
+    """
+    Make all elements in this tree none, signalling not to do any more layout.
+    """
     if lb is not None:
         if lb.parent is None:
             # Clear the solver.  Hopefully this garbage collects.
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
index 9a670b8231d9..d51b47acc588 100644
--- a/lib/matplotlib/contour.py
+++ b/lib/matplotlib/contour.py
@@ -132,18 +132,14 @@ def clabel(self, levels=None, *,
             A list of `.Text` instances for the labels.
         """
 
-        """
-        NOTES on how this all works:
-
-        clabel basically takes the input arguments and uses them to
-        add a list of "label specific" attributes to the ContourSet
-        object.  These attributes are all of the form label* and names
-        should be fairly self explanatory.
-
-        Once these attributes are set, clabel passes control to the
-        labels method (case of automatic label placement) or
-        `BlockingContourLabeler` (case of manual label placement).
-        """
+        # clabel basically takes the input arguments and uses them to
+        # add a list of "label specific" attributes to the ContourSet
+        # object.  These attributes are all of the form label* and names
+        # should be fairly self explanatory.
+        #
+        # Once these attributes are set, clabel passes control to the
+        # labels method (case of automatic label placement) or
+        # `BlockingContourLabeler` (case of manual label placement).
 
         self.labelFmt = fmt
         self._use_clabeltext = use_clabeltext
@@ -1496,12 +1492,8 @@ def _contour_args(self, args, kwargs):
 
     def _check_xyz(self, args, kwargs):
         """
-        For functions like contour, check that the dimensions
-        of the input arrays match; if x and y are 1D, convert
-        them to 2D using meshgrid.
-
-        Possible change: I think we should make and use an ArgumentError
-        Exception class (here and elsewhere).
+        Check that the shapes of the input arrays match; if x and y are 1D,
+        convert them to 2D using meshgrid.
         """
         x, y = args[:2]
         kwargs = self.ax._process_unit_info(xdata=x, ydata=y, kwargs=kwargs)
@@ -1513,39 +1505,34 @@ def _check_xyz(self, args, kwargs):
         z = ma.asarray(args[2], dtype=np.float64)
 
         if z.ndim != 2:
-            raise TypeError("Input z must be a 2D array.")
-        elif z.shape[0] < 2 or z.shape[1] < 2:
-            raise TypeError("Input z must be at least a 2x2 array.")
-        else:
-            Ny, Nx = z.shape
+            raise TypeError(f"Input z must be 2D, not {z.ndim}D")
+        if z.shape[0] < 2 or z.shape[1] < 2:
+            raise TypeError(f"Input z must be at least a (2, 2) array, but "
+                            f"has shape {z.shape}")
+        Ny, Nx = z.shape
 
         if x.ndim != y.ndim:
-            raise TypeError("Number of dimensions of x and y should match.")
-
+            raise TypeError(f"Dimensionalities of x ({x.ndim}) and y "
+                            f"({y.ndim}) do not match")
         if x.ndim == 1:
-
             nx, = x.shape
             ny, = y.shape
-
             if nx != Nx:
-                raise TypeError("Length of x must be number of columns in z.")
-
+                raise TypeError(f"Length of x ({nx}) must match number of "
+                                f"columns in z ({Nx})")
             if ny != Ny:
-                raise TypeError("Length of y must be number of rows in z.")
-
+                raise TypeError(f"Length of y ({ny}) must match number of "
+                                f"rows in z ({Ny})")
             x, y = np.meshgrid(x, y)
-
         elif x.ndim == 2:
-
             if x.shape != z.shape:
-                raise TypeError("Shape of x does not match that of z: found "
-                                "{0} instead of {1}.".format(x.shape, z.shape))
-
+                raise TypeError(
+                    f"Shapes of x {x.shape} and z {z.shape} do not match")
             if y.shape != z.shape:
-                raise TypeError("Shape of y does not match that of z: found "
-                                "{0} instead of {1}.".format(y.shape, z.shape))
+                raise TypeError(
+                    f"Shapes of y {y.shape} and z {z.shape} do not match")
         else:
-            raise TypeError("Inputs x and y must be 1D or 2D.")
+            raise TypeError(f"Inputs x and y must be 1D or 2D, not {x.ndim}D")
 
         return x, y, z
 
@@ -1563,9 +1550,10 @@ def _initialize_x_y(self, z):
         will give the minimum and maximum values of x and y.
         """
         if z.ndim != 2:
-            raise TypeError("Input must be a 2D array.")
+            raise TypeError(f"Input z must be 2D, not {z.ndim}D")
         elif z.shape[0] < 2 or z.shape[1] < 2:
-            raise TypeError("Input z must be at least a 2x2 array.")
+            raise TypeError(f"Input z must be at least a (2, 2) array, but "
+                            f"has shape {z.shape}")
         else:
             Ny, Nx = z.shape
         if self.origin is None:  # Not for image-matching.
diff --git a/lib/matplotlib/legend.py b/lib/matplotlib/legend.py
index ee754bd37379..231b6594e2e3 100644
--- a/lib/matplotlib/legend.py
+++ b/lib/matplotlib/legend.py
@@ -74,25 +74,18 @@ def artist_picker(self, legend, evt):
         return self.legend.contains(evt)
 
     def finalize_offset(self):
-        loc_in_canvas = self.get_loc_in_canvas()
-
-        if self._update == "loc":
-            self._update_loc(loc_in_canvas)
-        elif self._update == "bbox":
-            self._update_bbox_to_anchor(loc_in_canvas)
-        else:
-            raise RuntimeError("update parameter '%s' is not supported." %
-                               self.update)
+        update_method = cbook._check_getitem(
+            {"loc": self._update_loc, "bbox": self._bbox_to_anchor},
+            update=self._update)
+        update_method(self.get_loc_in_canvas())
 
     def _update_loc(self, loc_in_canvas):
         bbox = self.legend.get_bbox_to_anchor()
-
         # if bbox has zero width or height, the transformation is
-        # ill-defined. Fall back to the defaul bbox_to_anchor.
+        # ill-defined. Fall back to the default bbox_to_anchor.
         if bbox.width == 0 or bbox.height == 0:
             self.legend.set_bbox_to_anchor(None)
             bbox = self.legend.get_bbox_to_anchor()
-
         _bbox_transform = BboxTransformFrom(bbox)
         self.legend._loc = tuple(_bbox_transform.transform(loc_in_canvas))
 
diff --git a/lib/matplotlib/tests/test_animation.py b/lib/matplotlib/tests/test_animation.py
index f80d08e61d21..bb0ba2103219 100644
--- a/lib/matplotlib/tests/test_animation.py
+++ b/lib/matplotlib/tests/test_animation.py
@@ -5,7 +5,6 @@
 import weakref
 
 import numpy as np
-from pathlib import Path
 import pytest
 
 import matplotlib as mpl
diff --git a/lib/matplotlib/tests/test_colorbar.py b/lib/matplotlib/tests/test_colorbar.py
index ee95561986dc..84368cba8a8d 100644
--- a/lib/matplotlib/tests/test_colorbar.py
+++ b/lib/matplotlib/tests/test_colorbar.py
@@ -505,7 +505,7 @@ def test_colorbar_scale_reset():
     assert cbar.ax.yaxis.get_scale() == 'linear'
 
 
-def test_colorbar_get_ticks():
+def test_colorbar_get_ticks_2():
     with rc_context({'_internal.classic_mode': False}):
 
         fig, ax = plt.subplots()
diff --git a/lib/matplotlib/tests/test_contour.py b/lib/matplotlib/tests/test_contour.py
index 0bf4827e64d5..9c0979c33332 100644
--- a/lib/matplotlib/tests/test_contour.py
+++ b/lib/matplotlib/tests/test_contour.py
@@ -1,4 +1,5 @@
 import datetime
+import re
 
 import numpy as np
 from matplotlib.testing.decorators import image_comparison
@@ -29,93 +30,32 @@ def test_contour_shape_2d_valid():
     ax.contour(xg, yg, z)
 
 
-def test_contour_shape_mismatch_1():
-
-    x = np.arange(9)
-    y = np.arange(9)
-    z = np.random.random((9, 10))
-
-    fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(x, y, z)
-    excinfo.match(r'Length of x must be number of columns in z.')
-
-
-def test_contour_shape_mismatch_2():
-
-    x = np.arange(10)
-    y = np.arange(10)
-    z = np.random.random((9, 10))
-
+@pytest.mark.parametrize("args, message", [
+    ((np.arange(9), np.arange(9), np.empty((9, 10))),
+     'Length of x (9) must match number of columns in z (10)'),
+    ((np.arange(10), np.arange(10), np.empty((9, 10))),
+     'Length of y (10) must match number of rows in z (9)'),
+    ((np.empty((10, 10)), np.arange(10), np.empty((9, 10))),
+     'Dimensionalities of x (2) and y (1) do not match'),
+    ((np.arange(10), np.empty((10, 10)), np.empty((9, 10))),
+     'Dimensionalities of x (1) and y (2) do not match'),
+    ((np.empty((9, 9)), np.empty((9, 10)), np.empty((9, 10))),
+     'Shapes of x (9, 9) and z (9, 10) do not match'),
+    ((np.empty((9, 10)), np.empty((9, 9)), np.empty((9, 10))),
+     'Shapes of y (9, 9) and z (9, 10) do not match'),
+    ((np.empty((3, 3, 3)), np.empty((3, 3, 3)), np.empty((9, 10))),
+     'Inputs x and y must be 1D or 2D, not 3D'),
+    ((np.empty((3, 3, 3)), np.empty((3, 3, 3)), np.empty((3, 3, 3))),
+     'Input z must be 2D, not 3D'),
+    (([[0]],),  # github issue 8197
+     'Input z must be at least a (2, 2) array, but has shape (1, 1)'),
+    (([0], [0], [[0]]),
+     'Input z must be at least a (2, 2) array, but has shape (1, 1)'),
+])
+def test_contour_shape_error(args, message):
     fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(x, y, z)
-    excinfo.match(r'Length of y must be number of rows in z.')
-
-
-def test_contour_shape_mismatch_3():
-
-    x = np.arange(10)
-    y = np.arange(10)
-    xg, yg = np.meshgrid(x, y)
-    z = np.random.random((9, 10))
-
-    fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(xg, y, z)
-    excinfo.match(r'Number of dimensions of x and y should match.')
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(x, yg, z)
-    excinfo.match(r'Number of dimensions of x and y should match.')
-
-
-def test_contour_shape_mismatch_4():
-
-    g = np.random.random((9, 10))
-    b = np.random.random((9, 9))
-    z = np.random.random((9, 10))
-
-    fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(b, g, z)
-    excinfo.match(r'Shape of x does not match that of z: found \(9L?, 9L?\) ' +
-                  r'instead of \(9L?, 10L?\)')
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(g, b, z)
-    excinfo.match(r'Shape of y does not match that of z: found \(9L?, 9L?\) ' +
-                  r'instead of \(9L?, 10L?\)')
-
-
-def test_contour_shape_invalid_1():
-
-    x = np.random.random((3, 3, 3))
-    y = np.random.random((3, 3, 3))
-    z = np.random.random((9, 10))
-
-    fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(x, y, z)
-    excinfo.match(r'Inputs x and y must be 1D or 2D.')
-
-
-def test_contour_shape_invalid_2():
-
-    x = np.random.random((3, 3, 3))
-    y = np.random.random((3, 3, 3))
-    z = np.random.random((3, 3, 3))
-
-    fig, ax = plt.subplots()
-
-    with pytest.raises(TypeError) as excinfo:
-        ax.contour(x, y, z)
-    excinfo.match(r'Input z must be a 2D array.')
+    with pytest.raises(TypeError, match=re.escape(message)):
+        ax.contour(*args)
 
 
 def test_contour_empty_levels():
@@ -311,47 +251,31 @@ def test_contourf_symmetric_locator():
     assert_array_almost_equal(cs.levels, np.linspace(-12, 12, 5))
 
 
-def test_contour_1x1_array():
-    # github issue 8197
-    with pytest.raises(TypeError) as excinfo:
-        plt.contour([[0]])
-    excinfo.match(r'Input z must be at least a 2x2 array.')
-
-    with pytest.raises(TypeError) as excinfo:
-        plt.contour([0], [0], [[0]])
-    excinfo.match(r'Input z must be at least a 2x2 array.')
-
-
-def test_internal_cpp_api():
-    # Following github issue 8197.
+@pytest.mark.parametrize("args, cls, message", [
+    ((), TypeError,
+     'function takes exactly 6 arguments (0 given)'),
+    ((1, 2, 3, 4, 5, 6), ValueError,
+     'Expected 2-dimensional array, got 0'),
+    (([[0]], [[0]], [[]], None, True, 0), ValueError,
+     'x, y and z must all be 2D arrays with the same dimensions'),
+    (([[0]], [[0]], [[0]], None, True, 0), ValueError,
+     'x, y and z must all be at least 2x2 arrays'),
+    ((*[np.arange(4).reshape((2, 2))] * 3, [[0]], True, 0), ValueError,
+     'If mask is set it must be a 2D array with the same dimensions as x.'),
+])
+def test_internal_cpp_api(args, cls, message):  # Github issue 8197.
     import matplotlib._contour as _contour
+    with pytest.raises(cls, match=re.escape(message)):
+        _contour.QuadContourGenerator(*args)
 
-    with pytest.raises(TypeError) as excinfo:
-        qcg = _contour.QuadContourGenerator()
-    excinfo.match(r'function takes exactly 6 arguments \(0 given\)')
-
-    with pytest.raises(ValueError) as excinfo:
-        qcg = _contour.QuadContourGenerator(1, 2, 3, 4, 5, 6)
-    excinfo.match(r'Expected 2-dimensional array, got 0')
-
-    with pytest.raises(ValueError) as excinfo:
-        qcg = _contour.QuadContourGenerator([[0]], [[0]], [[]], None, True, 0)
-    excinfo.match(r'x, y and z must all be 2D arrays with the same dimensions')
-
-    with pytest.raises(ValueError) as excinfo:
-        qcg = _contour.QuadContourGenerator([[0]], [[0]], [[0]], None, True, 0)
-    excinfo.match(r'x, y and z must all be at least 2x2 arrays')
 
+def test_internal_cpp_api_2():
+    import matplotlib._contour as _contour
     arr = [[0, 1], [2, 3]]
-    with pytest.raises(ValueError) as excinfo:
-        qcg = _contour.QuadContourGenerator(arr, arr, arr, [[0]], True, 0)
-    excinfo.match(r'If mask is set it must be a 2D array with the same ' +
-                  r'dimensions as x.')
-
     qcg = _contour.QuadContourGenerator(arr, arr, arr, None, True, 0)
-    with pytest.raises(ValueError) as excinfo:
+    with pytest.raises(
+            ValueError, match=r'filled contour levels must be increasing'):
         qcg.create_filled_contour(1, 0)
-    excinfo.match(r'filled contour levels must be increasing')
 
 
 def test_circular_contour_warning():
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 690cf86b22bd..7f370c9051d1 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -2,7 +2,6 @@
 from copy import copy
 import io
 import os
-import sys
 from pathlib import Path
 import platform
 import sys
diff --git a/lib/matplotlib/widgets.py b/lib/matplotlib/widgets.py
index 644f662c361f..9051ff5bc8dd 100644
--- a/lib/matplotlib/widgets.py
+++ b/lib/matplotlib/widgets.py
@@ -769,7 +769,7 @@ def _rendercursor(self):
 
         widthtext = self.text[:self.cursor_index]
         no_text = False
-        if(widthtext == "" or widthtext == " " or widthtext == "  "):
+        if widthtext in ["", " ", "  "]:
             no_text = widthtext == ""
             widthtext = ","
 
@@ -1028,11 +1028,9 @@ def __init__(self, ax, labels, active=0, activecolor='blue'):
         axcolor = ax.get_facecolor()
 
         # scale the radius of the circle with the spacing between each one
-        circle_radius = (dy / 2) - 0.01
-
-        # defaul to hard-coded value if the radius becomes too large
-        if(circle_radius > 0.05):
-            circle_radius = 0.05
+        circle_radius = dy / 2 - 0.01
+        # default to hard-coded value if the radius becomes too large
+        circle_radius = min(circle_radius, 0.05)
 
         self.labels = []
         self.circles = []
diff --git a/lib/mpl_toolkits/tests/test_axes_grid1.py b/lib/mpl_toolkits/tests/test_axes_grid1.py
index 6537ae087e1c..f01eef6e6f7d 100644
--- a/lib/mpl_toolkits/tests/test_axes_grid1.py
+++ b/lib/mpl_toolkits/tests/test_axes_grid1.py
@@ -1,30 +1,24 @@
+from itertools import product
+import platform
+
 import matplotlib
 import matplotlib.pyplot as plt
+from matplotlib import cbook
 from matplotlib.cbook import MatplotlibDeprecationWarning
+from matplotlib.backend_bases import MouseEvent
+from matplotlib.colors import LogNorm
+from matplotlib.transforms import Bbox, TransformedBbox
 from matplotlib.testing.decorators import (
     image_comparison, remove_ticks_and_titles)
 
-from mpl_toolkits.axes_grid1 import host_subplot
-from mpl_toolkits.axes_grid1 import make_axes_locatable
-from mpl_toolkits.axes_grid1 import AxesGrid
-from mpl_toolkits.axes_grid1 import ImageGrid
-from mpl_toolkits.axes_grid1.inset_locator import (
-    zoomed_inset_axes,
-    mark_inset,
-    inset_axes,
-    BboxConnectorPatch
-)
+from mpl_toolkits.axes_grid1 import (
+    host_subplot, make_axes_locatable, AxesGrid, ImageGrid)
 from mpl_toolkits.axes_grid1.anchored_artists import (
-    AnchoredSizeBar,
-    AnchoredDirectionArrows)
-
-from matplotlib.backend_bases import MouseEvent
-from matplotlib.colors import LogNorm
-from matplotlib.transforms import Bbox, TransformedBbox
-from itertools import product
+    AnchoredSizeBar, AnchoredDirectionArrows)
+from mpl_toolkits.axes_grid1.inset_locator import (
+    zoomed_inset_axes, mark_inset, inset_axes, BboxConnectorPatch)
 
 import pytest
-import platform
 
 import numpy as np
 from numpy.testing import assert_array_equal, assert_array_almost_equal
@@ -125,18 +119,12 @@ def test_axesgrid_colorbar_log_smoketest(legacy_colorbar):
 
 @image_comparison(['inset_locator.png'], style='default', remove_text=True)
 def test_inset_locator():
-    def get_demo_image():
-        from matplotlib.cbook import get_sample_data
-        import numpy as np
-        f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
-        z = np.load(f)
-        # z is a numpy array of 15x15
-        return z, (-3, 4, -4, 3)
-
     fig, ax = plt.subplots(figsize=[5, 4])
 
     # prepare the demo image
-    Z, extent = get_demo_image()
+    # Z is a 15x15 array
+    Z = np.load(cbook.get_sample_data("axes_grid/bivariate_normal.npy"))
+    extent = (-3, 4, -4, 3)
     Z2 = np.zeros([150, 150], dtype="d")
     ny, nx = Z.shape
     Z2[30:30 + ny, 30:30 + nx] = Z
@@ -173,18 +161,12 @@ def get_demo_image():
 
 @image_comparison(['inset_axes.png'], style='default', remove_text=True)
 def test_inset_axes():
-    def get_demo_image():
-        from matplotlib.cbook import get_sample_data
-        import numpy as np
-        f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
-        z = np.load(f)
-        # z is a numpy array of 15x15
-        return z, (-3, 4, -4, 3)
-
     fig, ax = plt.subplots(figsize=[5, 4])
 
     # prepare the demo image
-    Z, extent = get_demo_image()
+    # Z is a 15x15 array
+    Z = np.load(cbook.get_sample_data("axes_grid/bivariate_normal.npy"))
+    extent = (-3, 4, -4, 3)
     Z2 = np.zeros([150, 150], dtype="d")
     ny, nx = Z.shape
     Z2[30:30 + ny, 30:30 + nx] = Z