matplotlib
diff --git a/‎lib/matplotlib/axes/_base.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_base.py
+19-8Lines changed: 19 additions & 8 deletions b/‎lib/matplotlib/axes/_base.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_base.py
+19-8Lines changed: 19 additions & 8 deletions
diff --git a/‎lib/matplotlib/tests/test_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_axes.py
+15Lines changed: 15 additions & 0 deletions b/‎lib/matplotlib/tests/test_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_axes.py
+15Lines changed: 15 additions & 0 deletions
@@ -2371,14 +2371,25 @@ def autoscale_view(self, tight=None, scalex=True, scaley=True):
         if tight is not None:
             self._tight = bool(tight)
 
-        if self.use_sticky_edges and (
-                (self._xmargin and scalex and self._autoscaleXon) or
-                (self._ymargin and scaley and self._autoscaleYon)):
-            stickies = [artist.sticky_edges for artist in self.get_children()]
-        else:  # Small optimization.
-            stickies = []
-        x_stickies = np.sort([x for sticky in stickies for x in sticky.x])
-        y_stickies = np.sort([y for sticky in stickies for y in sticky.y])
+        x_stickies = y_stickies = np.array([])
+        if self.use_sticky_edges:
+            # Only iterate over axes and artists if needed.  The check for
+            # ``hasattr(ax, "lines")`` is necessary because this can be called
+            # very early in the axes init process (e.g., for twin axes) when
+            # these attributes don't even exist yet, in which case
+            # `get_children` would raise an AttributeError.
+            if self._xmargin and scalex and self._autoscaleXon:
+                x_stickies = np.sort(np.concatenate([
+                    artist.sticky_edges.x
+                    for ax in self._shared_x_axes.get_siblings(self)
+                    if hasattr(ax, "lines")
+                    for artist in ax.get_children()]))
+            if self._ymargin and scaley and self._autoscaleYon:
+                y_stickies = np.sort(np.concatenate([
+                    artist.sticky_edges.y
+                    for ax in self._shared_y_axes.get_siblings(self)
+                    if hasattr(ax, "lines")
+                    for artist in ax.get_children()]))
         if self.get_xscale().lower() == 'log':
             x_stickies = x_stickies[x_stickies > 0]
         if self.get_yscale().lower() == 'log':
 
@@ -334,6 +334,21 @@ def test_use_sticky_edges():
     assert_allclose(ax.get_ylim(), (-0.5, 1.5))
 
 
+@check_figures_equal(extensions=["png"])
+def test_sticky_shared_axes(fig_test, fig_ref):
+    # Check that sticky edges work whether they are set in an axes that is a
+    # "master" in a share, or an axes that is a "follower".
+    Z = np.arange(15).reshape(3, 5)
+
+    ax0 = fig_test.add_subplot(211)
+    ax1 = fig_test.add_subplot(212, sharex=ax0)
+    ax1.pcolormesh(Z)
+
+    ax0 = fig_ref.add_subplot(212)
+    ax1 = fig_ref.add_subplot(211, sharex=ax0)
+    ax0.pcolormesh(Z)
+
+
 @image_comparison(['offset_points'], remove_text=True)
 def test_basic_annotate():
     # Setup some data