BUG: sanitize norm extrema to be floats

Nathan Goldbaum · Nathan Goldbaum · commit 64351f572e0f · 2018-03-08T12:17:23.000-06:00
diff --git a/lib/matplotlib/cm.py b/lib/matplotlib/cm.py
@@ -314,9 +314,9 @@ def set_clim(self, vmin=None, vmax=None):
             except (TypeError, ValueError):
                 pass
         if vmin is not None:
-            self.norm.vmin = vmin
+            self.norm.vmin = colors._sanitize_extrema(vmin)
         if vmax is not None:
-            self.norm.vmax = vmax
+            self.norm.vmax = colors._sanitize_extrema(vmax)
         self.changed()
 
     def set_cmap(self, cmap):
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -94,6 +94,16 @@ def get_named_colors_mapping():
     return _colors_full_map
 
 
+def _sanitize_extrema(ex):
+    if ex is None:
+        return ex
+    try:
+        ret = np.asscalar(ex)
+    except AttributeError:
+        ret = float(ex)
+    return ret
+
+
 def _is_nth_color(c):
     """Return whether *c* can be interpreted as an item in the color cycle."""
     return isinstance(c, six.string_types) and re.match(r"\AC[0-9]\Z", c)
@@ -878,8 +888,8 @@ def __init__(self, vmin=None, vmax=None, clip=False):
         likely to lead to surprises; therefore the default is
         *clip* = *False*.
         """
-        self.vmin = vmin
-        self.vmax = vmax
+        self.vmin = _sanitize_extrema(vmin)
+        self.vmax = _sanitize_extrema(vmax)
         self.clip = clip
 
     @staticmethod
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -686,12 +686,21 @@ def __isub__(self, other):
         def __add__(self, other):
             raise RuntimeError
 
+        def __getitem__(self, index):
+            ret = super(MyArray, self).__getitem__(index)
+            if ret.shape == ():
+                ret = np.array(ret)
+            return ret.view(MyArray)
+
     data = np.arange(-10, 10, 1, dtype=float)
+    mydata = data.view(MyArray)
 
     for norm in [mcolors.Normalize(), mcolors.LogNorm(),
                  mcolors.SymLogNorm(3, vmax=5, linscale=1),
+                 mcolors.Normalize(vmin=mydata.max(), vmax=mydata.max()),
+                 mcolors.SymLogNorm(3, vmin=mydata.max(), vmax=mydata.max()),
                  mcolors.PowerNorm(1)]:
-        assert_array_equal(norm(data.view(MyArray)), norm(data))
+        assert_array_equal(norm(mydata), norm(data))
         if isinstance(norm, mcolors.PowerNorm):
             assert len(recwarn) == 1
             warn = recwarn.pop(UserWarning)
