Fix removal of (Sub)Figure suplabels

QuLogic · QuLogic · commit 35496a76c4a4 · 2026-02-04T06:06:23.000-05:00
In such cases, we need to override the default `_remove_method` to ensure that the (Sub)Figure attributes are also cleared. Fixes matplotlib#31073
diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
@@ -376,6 +376,13 @@ def _suplabels(self, t, info, **kwargs):
         else:
             suplab = self.text(x, y, t, **kwargs)
             setattr(self, info['name'], suplab)
+            orig_remove_method = suplab._remove_method
+
+            # Ensure sublabel is properly removed from Figure internals.
+            def _remove(label):
+                orig_remove_method(label)
+                setattr(self, info['name'], None)
+            suplab._remove_method = _remove
         suplab._autopos = autopos
         self.stale = True
         return suplab
diff --git a/lib/matplotlib/tests/test_figure.py b/lib/matplotlib/tests/test_figure.py
@@ -357,12 +357,18 @@ def test_get_suptitle_supxlabel_supylabel():
     assert fig.get_suptitle() == ""
     assert fig.get_supxlabel() == ""
     assert fig.get_supylabel() == ""
-    fig.suptitle('suptitle')
+    text = fig.suptitle('suptitle')
     assert fig.get_suptitle() == 'suptitle'
-    fig.supxlabel('supxlabel')
+    text.remove()
+    assert fig.get_suptitle() == ''
+    text = fig.supxlabel('supxlabel')
     assert fig.get_supxlabel() == 'supxlabel'
-    fig.supylabel('supylabel')
+    text.remove()
+    assert fig.get_supxlabel() == ''
+    text = fig.supylabel('supylabel')
     assert fig.get_supylabel() == 'supylabel'
+    text.remove()
+    assert fig.get_supylabel() == ''
 
 
 @image_comparison(['alpha_background'],
@@ -1340,6 +1346,10 @@ def test_subfigure():
     sub[0].suptitle('Left Side')
     sub[0].set_facecolor('white')
 
+    # Check that removing a suplabel on a subfigure works.
+    label = sub[0].supxlabel('Should not exist')
+    label.remove()
+
     axs = sub[1].subplots(1, 3)
     for ax in axs.flat:
         pc = ax.pcolormesh(np.random.randn(30, 30), vmin=-2, vmax=2)
