Move empty hexbin fix to make_norm_from_scale.

3d2ffef added special-casing to handle empty log-scale hexbins, but the
more back-compatible fix is to switch make_norm_from_scale to reproduce
the old behavior of setting vmin/vmax to np.ma.masked when autoscaling
with an empty array.  (Whether that behavior is really better is
unclear, but until this is properly investigated, it seems safer to go
back to it.)

Author: anntzer

lib/matplotlib/axes/_axes.py

@@ -4993,9 +4993,7 @@ def reduce_C_function(C: array) -> float
         # autoscale the norm with current accum values if it hasn't been set
         if norm is not None:
             if norm.vmin is None and norm.vmax is None:
-                norm.autoscale_None(accum)
-            norm.vmin = np.ma.masked if norm.vmin is None else norm.vmin
-            norm.vmax = np.ma.masked if norm.vmax is None else norm.vmax
+                norm.autoscale(accum)
 
         if bins is not None:
             if not np.iterable(bins):

lib/matplotlib/colors.py

@@ -1718,10 +1718,14 @@ def inverse(self, value):
         def autoscale(self, A):
             # i.e. A[np.isfinite(...)], but also for non-array A's
             in_trf_domain = np.extract(np.isfinite(self._trf.transform(A)), A)
+            if in_trf_domain.size == 0:
+                in_trf_domain = np.ma.masked
             return super().autoscale(in_trf_domain)
 
         def autoscale_None(self, A):
             in_trf_domain = np.extract(np.isfinite(self._trf.transform(A)), A)
+            if in_trf_domain.size == 0:
+                in_trf_domain = np.ma.masked
             return super().autoscale_None(in_trf_domain)
 
     if base_norm_cls is Normalize: