matplotlib
diff --git a/‎lib/matplotlib/path.py
Copy file name to clipboardExpand all lines: lib/matplotlib/path.py
+10-6Lines changed: 10 additions & 6 deletions b/‎lib/matplotlib/path.py
Copy file name to clipboardExpand all lines: lib/matplotlib/path.py
+10-6Lines changed: 10 additions & 6 deletions
diff --git a/‎lib/matplotlib/tests/test_path.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_path.py
+21-9Lines changed: 21 additions & 9 deletions b/‎lib/matplotlib/tests/test_path.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_path.py
+21-9Lines changed: 21 additions & 9 deletions
@@ -22,9 +22,8 @@
 
 import numpy as np
 
-from matplotlib import _path
-from matplotlib.cbook import simple_linear_interpolation, maxdict
-from matplotlib import rcParams
+from . import _path, rcParams
+from .cbook import simple_linear_interpolation, maxdict
 
 
 class Path(object):
@@ -493,9 +492,14 @@ def contains_point(self, point, transform=None, radius=0.0):
         """
         if transform is not None:
             transform = transform.frozen()
-        result = _path.point_in_path(point[0], point[1], radius, self,
-                                     transform)
-        return result
+        # `point_in_path` does not handle nonlinear transforms, so we
+        # transform the path ourselves.  If `transform` is affine, letting
+        # `point_in_path` handle the transform avoids allocating an extra
+        # buffer.
+        if transform and not transform.is_affine:
+            self = transform.transform_path(self)
+            transform = None
+        return _path.point_in_path(point[0], point[1], radius, self, transform)
 
     def contains_points(self, points, transform=None, radius=0.0):
         """
 
@@ -45,6 +45,27 @@ def test_contains_points_negative_radius():
     assert np.all(result == expected)
 
 
+def test_point_in_path_nan():
+    box = np.array([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]])
+    p = Path(box)
+    test = np.array([[np.nan, 0.5]])
+    contains = p.contains_points(test)
+    assert len(contains) == 1
+    assert not contains[0]
+
+
+def test_nonlinear_containment():
+    fig, ax = plt.subplots()
+    ax.set(xscale="log", ylim=(0, 1))
+    polygon = ax.axvspan(1, 10)
+    assert polygon.get_path().contains_point(
+        ax.transData.transform_point((5, .5)), ax.transData)
+    assert not polygon.get_path().contains_point(
+        ax.transData.transform_point((.5, .5)), ax.transData)
+    assert not polygon.get_path().contains_point(
+        ax.transData.transform_point((50, .5)), ax.transData)
+
+
 @image_comparison(baseline_images=['path_clipping'],
                   extensions=['svg'], remove_text=True)
 def test_path_clipping():
@@ -66,15 +87,6 @@ def test_path_clipping():
             xy, facecolor='none', edgecolor='red', closed=True))
 
 
-def test_point_in_path_nan():
-    box = np.array([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]])
-    p = Path(box)
-    test = np.array([[np.nan, 0.5]])
-    contains = p.contains_points(test)
-    assert len(contains) == 1
-    assert not contains[0]
-
-
 @image_comparison(baseline_images=['semi_log_with_zero'], extensions=['png'])
 def test_log_transform_with_zero():
     x = np.arange(-10, 10)