Deprecate allowing scalars for fill_between where

timhoffm · timhoffm · commit 5345cb696d99 · 2019-07-22T20:55:00.000+02:00
diff --git a/doc/api/next_api_changes/2019-06-09-TH.rst b/doc/api/next_api_changes/2019-06-09-TH.rst
@@ -0,0 +1,8 @@
+Passing scalars to parameter where in ``fill_between()`` and ``fill_betweenx()``
+````````````````````````````````````````````````````````````````````````````````
+
+Passing scalars to parameter *where* in ``fill_between()`` and
+``fill_betweenx()`` is deprecated. While the documentation already states that
+*where* must be of the same size as *x* (or *y*), scalars were accepted and
+broadcasted to the size of *x*. Non-matching sizes will raise a ``ValueError``
+in the future.
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -5175,6 +5175,14 @@ def fill_between(self, x, y1, y2=0, where=None, interpolate=False,
 
         if where is None:
             where = True
+        else:
+            where = np.asarray(where, dtype=bool)
+            if where.size != x.size:
+                cbook.warn_deprecated(
+                    "3.2",
+                    message="The parameter where must have the same size as x "
+                            "in fill_between(). This will become an error in "
+                            "future versions of Matplotlib.")
         where = where & ~functools.reduce(np.logical_or,
                                           map(np.ma.getmask, [x, y1, y2]))
 
@@ -5356,6 +5364,14 @@ def fill_betweenx(self, y, x1, x2=0, where=None,
 
         if where is None:
             where = True
+        else:
+            where = np.asarray(where, dtype=bool)
+            if where.size != y.size:
+                cbook.warn_deprecated(
+                    "3.2",
+                    message="The parameter where must have the same size as y "
+                            "in fill_between(). This will become an error in "
+                            "future versions of Matplotlib.")
         where = where & ~functools.reduce(np.logical_or,
                                           map(np.ma.getmask, [y, x1, x2]))
 
