Merge branch 'master' of https://github.com/matplotlib/matplotlib

surana-mudit · surana-mudit · commit 8fbadcee5cb5 · 2018-01-04T13:22:51.000+05:30
diff --git a/doc/faq/howto_faq.rst b/doc/faq/howto_faq.rst
@@ -19,10 +19,11 @@ Plotting: howto
 Plot `numpy.datetime64` values
 ------------------------------
 
-For Matplotlib to plot dates (or any scalar with units) a converter
-to float needs to be registered with the `matplolib.units` module.  The
-current best converters for `datetime64` values are in `pandas`. To enable the
-converter, import it from pandas::
+As of Matplotlib 2.2, `numpy.datetime64` objects are handled the same way
+as `datetime.datetime` objects.
+
+If you prefer the pandas converters and locators, you can register their
+converter with the `matplolib.units` module::
 
   from pandas.tseries import converter as pdtc
   pdtc.register()
diff --git a/examples/lines_bars_and_markers/arctest.py b/examples/lines_bars_and_markers/arctest.py
@@ -18,7 +18,7 @@ def f(t):
 t1 = np.arange(0.0, 5.0, .2)
 
 l = plt.plot(t1, f(t1), 'ro')
-plt.setp(l, 'markersize', 30)
-plt.setp(l, 'markerfacecolor', 'C0')
+plt.setp(l, markersize=30)
+plt.setp(l, markerfacecolor='C0')
 
 plt.show()
diff --git a/examples/lines_bars_and_markers/stem_plot.py b/examples/lines_bars_and_markers/stem_plot.py
@@ -10,6 +10,6 @@
 
 x = np.linspace(0.1, 2 * np.pi, 10)
 markerline, stemlines, baseline = plt.stem(x, np.cos(x), '-.')
-plt.setp(baseline, 'color', 'r', 'linewidth', 2)
+plt.setp(baseline, color='r', linewidth=2)
 
 plt.show()
diff --git a/lib/matplotlib/patches.py b/lib/matplotlib/patches.py
@@ -143,14 +143,30 @@ def contains(self, mouseevent, radius=None):
 
     def contains_point(self, point, radius=None):
         """
-        Returns *True* if the given point is inside the path
+        Returns ``True`` if the given *point* is inside the path
         (transformed with its transform attribute).
+
+        *radius* allows the path to be made slightly larger or smaller.
         """
         radius = self._process_radius(radius)
         return self.get_path().contains_point(point,
                                               self.get_transform(),
                                               radius)
 
+    def contains_points(self, points, radius=None):
+        """
+        Returns a bool array which is ``True`` if the (closed) path
+        contains the corresponding point.
+        (transformed with its transform attribute).
+
+        *points* must be Nx2 array.
+        *radius* allows the path to be made slightly larger or smaller.
+        """
+        radius = self._process_radius(radius)
+        return self.get_path().contains_points(points,
+                                               self.get_transform(),
+                                               radius)
+
     def update_from(self, other):
         """
         Updates this :class:`Patch` from the properties of *other*.
diff --git a/lib/matplotlib/tests/test_patches.py b/lib/matplotlib/tests/test_patches.py
@@ -386,3 +386,27 @@ def test_datetime_datetime_fails():
 
     with pytest.raises(TypeError):
         mpatches.Rectangle((0, start), 1, dt_delta)
+
+
+def test_contains_point():
+    ell = mpatches.Ellipse((0.5, 0.5), 0.5, 1.0, 0)
+    points = [(0.0, 0.5), (0.2, 0.5), (0.25, 0.5), (0.5, 0.5)]
+    path = ell.get_path()
+    transform = ell.get_transform()
+    radius = ell._process_radius(None)
+    expected = np.array([path.contains_point(point,
+                                             transform,
+                                             radius) for point in points])
+    result = np.array([ell.contains_point(point) for point in points])
+    assert np.all(result == expected)
+
+
+def test_contains_points():
+    ell = mpatches.Ellipse((0.5, 0.5), 0.5, 1.0, 0)
+    points = [(0.0, 0.5), (0.2, 0.5), (0.25, 0.5), (0.5, 0.5)]
+    path = ell.get_path()
+    transform = ell.get_transform()
+    radius = ell._process_radius(None)
+    expected = path.contains_points(points, transform, radius)
+    result = ell.contains_points(points)
+    assert np.all(result == expected)
