FIX: process lists for inverse norms

Co-authored-by: QuLogic <[email protected]>

Author: jklymak

lib/matplotlib/colors.py

@@ -1449,12 +1449,14 @@ def inverse(self, value):
             t_vmin, t_vmax = self._trf.transform([self.vmin, self.vmax])
             if not np.isfinite([t_vmin, t_vmax]).all():
                 raise ValueError("Invalid vmin or vmax")
+            value, is_scalar = self.process_value(value)
             rescaled = value * (t_vmax - t_vmin)
             rescaled += t_vmin
-            return (self._trf
-                    .inverted()
-                    .transform(rescaled)
-                    .reshape(np.shape(value)))
+            value = (self._trf
+                     .inverted()
+                     .transform(rescaled)
+                     .reshape(np.shape(value)))
+            return value[0] if is_scalar else value
 
     Norm.__name__ = base_norm_cls.__name__
     Norm.__qualname__ = base_norm_cls.__qualname__

lib/matplotlib/tests/test_colors.py

@@ -460,6 +460,17 @@ def test_LogNorm():
     assert_array_equal(ln([1, 6]), [0, 1.0])
 
 
+def test_LogNorm_inverse():
+    """
+    Test that lists work, and that the inverse works
+    """
+    norm = mcolors.LogNorm(vmin=0.1, vmax=10)
+    assert_array_almost_equal(norm([0.5, 0.4]), [0.349485, 0.30103])
+    assert_array_almost_equal([0.5, 0.4], norm.inverse([0.349485, 0.30103]))
+    assert_array_almost_equal(norm(0.4), [0.30103])
+    assert_array_almost_equal([0.4], norm.inverse([0.30103]))
+
+
 def test_PowerNorm():
     a = np.array([0, 0.5, 1, 1.5], dtype=float)
     pnorm = mcolors.PowerNorm(1)