Fix make_norm_from_scale __name__ when used inline.

`make_norm_from_scale` can be used "inline", rather than as a class
decorator, to dynamically create norm classes.  However, in that case,
the second parameter (`base_norm_cls`) would normally be set to the root
base norm class (`mcolors.Normalize`).  In that case, we should
generate a new `__name__` for the dynamically generated class, to avoid
the slightly confusing situation of having two different classes both
called `mcolors.Normalize`.

Author: anntzer

lib/matplotlib/colors.py

@@ -1561,7 +1561,8 @@ def inverse(self, value):
                      .reshape(np.shape(value)))
             return value[0] if is_scalar else value
 
-    Norm.__name__ = base_norm_cls.__name__
+    Norm.__name__ = (f"{scale_cls.__name__}Norm" if base_norm_cls is Normalize
+                     else base_norm_cls.__name__)
     Norm.__qualname__ = base_norm_cls.__qualname__
     Norm.__module__ = base_norm_cls.__module__
     Norm.__doc__ = base_norm_cls.__doc__

lib/matplotlib/tests/test_colors.py

@@ -1475,3 +1475,9 @@ def test_norm_update_figs(fig_test, fig_ref):
     # Force initial draw to make sure it isn't already stale
     fig_test.canvas.draw()
     norm.vmin, norm.vmax = 10, 90
+
+
+def test_make_norm_from_scale_name():
+    logitnorm = mcolors.make_norm_from_scale(
+        mscale.LogitScale, mcolors.Normalize)
+    assert logitnorm.__name__ == "LogitScaleNorm"