Updates based on feedback from @QuLogic

trygvrad · trygvrad · commit eb37db805aae · 2025-09-10T23:44:58.000+02:00
diff --git a/lib/matplotlib/colorizer.py b/lib/matplotlib/colorizer.py
@@ -24,7 +24,7 @@
 import numpy as np
 from numpy import ma
 
-from matplotlib import _api, colors, cbook, artist, cm, scale
+from matplotlib import _api, colors, cbook, artist, scale
 import matplotlib as mpl
 
 mpl._docstring.interpd.register(
@@ -222,9 +222,9 @@ def _set_cmap(self, cmap):
         in_init = self._cmap is None
         cmap_obj = _ensure_cmap(cmap, accept_multivariate=True)
         if not in_init and self.norm.n_components != cmap_obj.n_variates:
-                raise ValueError(f"The colormap {cmap} does not support "
-                                 f"{self.norm.n_components} variates as required by "
-                                 f"the {type(self.norm)} on this Colorizer")
+            raise ValueError(f"The colormap {cmap} does not support "
+                             f"{self.norm.n_components} variates as required by "
+                             f"the {type(self.norm)} on this Colorizer")
         self._cmap = cmap_obj
         if not in_init:
             self.changed()  # Things are not set up properly yet.
@@ -814,7 +814,8 @@ def _ensure_cmap(cmap, accept_multivariate=False):
     if isinstance(cmap, types):
         return cmap
 
-    cmap_name = cmap if cmap is not None else mpl.rcParams["image.cmap"]
+    cmap_name = mpl._val_or_rc(cmap, "image.cmap")
+
     for mapping in mappings:
         if cmap_name in mapping:
             return mapping[cmap_name]
@@ -829,8 +830,6 @@ def _ensure_cmap(cmap, accept_multivariate=False):
                      " `matplotlib.multivar_colormaps()` for"
                      " bivariate and multivariate colormaps")
 
-    return cm.colormaps[cmap_name]
-
 
 def _ensure_multivariate_data(data, n_components):
     """
@@ -870,7 +869,8 @@ def _ensure_multivariate_data(data, n_components):
                 dt = np.dtype('float64, float64')
             else:
                 dt = np.dtype('float32, float32')
-            reconstructed = np.ma.frombuffer(data.data, dtype=dt).reshape(data.shape)
+
+            reconstructed = np.ma.array(np.asarray(data).view(dt))
             if np.ma.is_masked(data):
                 for descriptor in dt.descr:
                     reconstructed[descriptor[0]][data.mask] = np.ma.masked
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -2105,16 +2105,16 @@ def test_ensure_multivariate_data():
     assert mdata.dtype.fields['f1'][0] == np.int64
 
     # test input of floats, ints as tuple of lists
-    data = ([0.0, 0], [1, 1])
+    data = ([0.0, 0.0], [1, 1])
     mdata = mcolorizer._ensure_multivariate_data(data, 2)
     assert mdata.shape == (2,)
     assert mdata.dtype.fields['f0'][0] == np.float64
     assert mdata.dtype.fields['f1'][0] == np.int64
 
     # test input of array of floats
-    data = np.array([[0.0, 0], [1, 1]])
+    data = np.array([[0.0, 0, 0], [1, 1, 1]])
     mdata = mcolorizer._ensure_multivariate_data(data, 2)
-    assert mdata.shape == (2,)
+    assert mdata.shape == (3,)
     assert mdata.dtype.fields['f0'][0] == np.float64
     assert mdata.dtype.fields['f1'][0] == np.float64
 
