diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
index 4606e5c01aec..a29583668a17 100644
--- a/lib/matplotlib/axes/_base.py
+++ b/lib/matplotlib/axes/_base.py
@@ -2962,22 +2962,16 @@ def handle_single_axis(
# Prevent margin addition from crossing a sticky value. A small
# tolerance must be added due to floating point issues with
- # streamplot; it is defined relative to x0, x1, x1-x0 but has
+ # streamplot; it is defined relative to x1-x0 but has
# no absolute term (e.g. "+1e-8") to avoid issues when working with
# datasets where all values are tiny (less than 1e-8).
- tol = 1e-5 * max(abs(x0), abs(x1), abs(x1 - x0))
+ tol = 1e-5 * abs(x1 - x0)
# Index of largest element < x0 + tol, if any.
i0 = stickies.searchsorted(x0 + tol) - 1
x0bound = stickies[i0] if i0 != -1 else None
- # Ensure the boundary acts only if the sticky is the extreme value
- if x0bound is not None and x0bound > x0:
- x0bound = None
# Index of smallest element > x1 - tol, if any.
i1 = stickies.searchsorted(x1 - tol)
x1bound = stickies[i1] if i1 != len(stickies) else None
- # Ensure the boundary acts only if the sticky is the extreme value
- if x1bound is not None and x1bound < x1:
- x1bound = None
# Add the margin in figure space and then transform back, to handle
# non-linear scales.
diff --git a/lib/matplotlib/tests/baseline_images/test_axes/sticky_tolerance_cf.png b/lib/matplotlib/tests/baseline_images/test_axes/sticky_tolerance_cf.png
new file mode 100644
index 000000000000..a2e185c2769d
Binary files /dev/null and b/lib/matplotlib/tests/baseline_images/test_axes/sticky_tolerance_cf.png differ
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 13c181b68492..3791763f323f 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -701,6 +701,16 @@ def test_sticky_tolerance():
axs.flat[3].barh(y=1, width=width, left=-20000.1)
+@image_comparison(['sticky_tolerance_cf.png'], remove_text=True, style="mpl20")
+def test_sticky_tolerance_contourf():
+ fig, ax = plt.subplots()
+
+ x = y = [14496.71, 14496.75]
+ data = [[0, 1], [2, 3]]
+
+ ax.contourf(x, y, data)
+
+
def test_nargs_stem():
with pytest.raises(TypeError, match='0 were given'):
# stem() takes 1-3 arguments.
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