ENH: pick the middle color only 1 region with BoundaryNorm

tacaswell · tacaswell · commit a5f531791c0d · 2020-07-04T18:14:39.000-04:00
This never worked before so is not an API change.
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -1511,17 +1511,15 @@ def __call__(self, value, clip=None):
         # in the middle) such that the first region is mapped to the
         # first color and the last region is mapped to the last color.
         if self.Ncmap > self._n_regions:
-            # the maximum possible value in iret
-            divsor = self._n_regions - 1
-            if divsor == 0:
-                # special case the 1 region case, don't scale anything
-                scalefac = 1
+            if self._n_regions == 1:
+                # special case the 1 region case, pick the middle color
+                iret[iret == 0] = (self.Ncmap - 1) // 2
             else:
                 # otherwise linearly remap the values from the region index
                 # to the color index spaces
-                scalefac = (self.Ncmap - 1) / divsor
-            # do the scaling and re-cast to integers
-            iret = (iret * scalefac).astype(np.int16)
+                iret = (self.Ncmap - 1) / (self._n_regions - 1) * iret
+        # cast to 16bit integers in all cases
+        iret = iret.astype(np.int16)
         iret[xx < self.vmin] = -1
         iret[xx >= self.vmax] = max_col
         ret = np.ma.array(iret, mask=mask)
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -208,7 +208,7 @@ def test_BoundaryNorm():
     assert_array_equal(bn(vals), expected)
 
     # with a single region and interpolation
-    expected = [-1, 0, 0, 0, 3, 3]
+    expected = [-1, 1, 1, 1, 3, 3]
     bn = mcolors.BoundaryNorm([0, 2.2], ncolors)
     assert_array_equal(bn(vals), expected)
 
