More intelligent linspace based on cmap.N

kdpenner · kdpenner · commit 0d08213fee87 · 2020-05-19T17:01:48.000-04:00
diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
@@ -893,24 +893,25 @@ def _process_values(self, b=None):
         if b is not None:
             self._boundaries = np.asarray(b, dtype=float)
             if self.values is None and self.boundaries is not None:
-                # define the outside indices
+                # define the outside additions
                 if self.extend == 'min':
-                    i = 0
+                    to_add = self._boundaries[0]
                 elif self.extend == 'max':
-                    i = -1
+                    to_add = self._boundaries[-1]
                 elif self.extend == 'both':
-                    i = [0, -1]
+                    to_add = self._boundaries[[0, -1]]
                 elif self.extend == 'neither':
-                    i = slice(None)
+                    to_add = []
                 # add values to the colorbar insides
                 boundaries_inside = self._boundaries[self._inside]
+                n_between = max((self.cmap.N-len(to_add))// \
+                                (len(boundaries_inside)-1), 1)
                 self._values = np.linspace(boundaries_inside[:-1],
                                            np.roll(boundaries_inside, -1)[:-1],
-                                           1000, endpoint = False,
-                                           axis = -1).flatten()
+                                           n_between, endpoint=False,
+                                           axis=-1).flatten()
                 self._values = np.append(self._values, boundaries_inside[-1])
                 # add back in the boundaries for the extensions
-                to_add = np.atleast_1d(self._boundaries[i])
                 self._boundaries = np.sort(np.concatenate([to_add,
                                                            self._values]))
                 # calculate values at which to plot colors
