Simplify: decouple warning from filter, fix edge cases

- Move _warn_missing_groups call before the na_color guard so the
  warning fires regardless of na_color (not just when na_color is
  transparent).
- Remove col_for_color param from _filter_groups_transparent_na
  (warning is no longer its responsibility).
- Fix fallback column label: "in column." → "in the color column."
- Guard sorted() with try/except for non-sortable category types.
- Deduplicate set(groups_list) into a single groups_set variable.
- Parametrize tests over na_color=[None, "red"] to cover both paths.
- Add labels warning test.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: timtreis

src/spatialdata_plot/pl/render.py

@@ -114,36 +114,41 @@ def _warn_missing_groups(
     col_for_color: str | None = None,
 ) -> None:
     """Warn when ``groups`` contains values absent from the color column's categories."""
-    groups_list = [groups] if isinstance(groups, str) else list(groups)
-    missing = set(groups_list) - set(color_source_vector.categories)
+    groups_set = {groups} if isinstance(groups, str) else set(groups)
+    missing = groups_set - set(color_source_vector.categories)
     if not missing:
         return
-    col_label = f" '{col_for_color}'" if col_for_color else ""
-    if missing == set(groups_list):
+    col_label = f" '{col_for_color}'" if col_for_color else " the color column"
+    try:
+        missing_str = str(sorted(missing))
+    except TypeError:
+        missing_str = str(list(missing))
+    if missing == groups_set:
         logger.warning(
-            f"None of the requested groups {sorted(missing)} were found in column{col_label}. "
+            f"None of the requested groups {missing_str} were found in{col_label}. "
             "This usually means `groups` refers to values from a different column than `color`. "
             "The `groups` parameter selects categories of the column specified via `color`."
         )
     else:
+        try:
+            cats_str = str(sorted(color_source_vector.categories))
+        except TypeError:
+            cats_str = str(list(color_source_vector.categories))
         logger.warning(
-            f"Groups {sorted(missing)} were not found in column{col_label} and will be ignored. "
-            f"Available categories: {sorted(color_source_vector.categories)}."
+            f"Groups {missing_str} were not found in{col_label} and will be ignored. Available categories: {cats_str}."
         )
 
 
 def _filter_groups_transparent_na(
     groups: str | list[str],
     color_source_vector: pd.Categorical,
     color_vector: pd.Series | np.ndarray | list[str],
-    col_for_color: str | None = None,
 ) -> tuple[np.ndarray, pd.Categorical, np.ndarray]:
     """Return a boolean mask and filtered color vectors for groups filtering.
 
     Used when ``na_color=None`` (fully transparent) so that non-matching
     elements are removed entirely instead of rendered invisibly.
     """
-    _warn_missing_groups(groups, color_source_vector, col_for_color)
     keep = color_source_vector.isin(groups)
     filtered_csv = color_source_vector[keep]
     filtered_cv = np.asarray(color_vector)[keep]
@@ -324,12 +329,15 @@ def _render_shapes(
 
     values_are_categorical = color_source_vector is not None
 
+    if groups is not None and color_source_vector is not None:
+        _warn_missing_groups(groups, color_source_vector, col_for_color)
+
     # When groups are specified, filter out non-matching elements by default.
     # Only show non-matching elements if the user explicitly sets na_color.
     _na = render_params.cmap_params.na_color
     if groups is not None and color_source_vector is not None and (_na.default_color_set or _na.alpha == "00"):
         keep, color_source_vector, color_vector = _filter_groups_transparent_na(
-            groups, color_source_vector, color_vector, col_for_color=col_for_color
+            groups, color_source_vector, color_vector
         )
         shapes = shapes[keep].reset_index(drop=True)
         if len(shapes) == 0:
@@ -776,12 +784,15 @@ def _render_points(
     if added_color_from_table and col_for_color is not None:
         _reparse_points(sdata_filt, element, points_pd_with_color, transformation_in_cs, coordinate_system)
 
+    if groups is not None and color_source_vector is not None:
+        _warn_missing_groups(groups, color_source_vector, col_for_color)
+
     # When groups are specified, filter out non-matching elements by default.
     # Only show non-matching elements if the user explicitly sets na_color.
     _na = render_params.cmap_params.na_color
     if groups is not None and color_source_vector is not None and (_na.default_color_set or _na.alpha == "00"):
         keep, color_source_vector, color_vector = _filter_groups_transparent_na(
-            groups, color_source_vector, color_vector, col_for_color=col_for_color
+            groups, color_source_vector, color_vector
         )
         n_points = int(keep.sum())
         if n_points == 0:
@@ -1324,6 +1335,9 @@ def _render_labels(
         else:
             assert color_source_vector is None
 
+    if groups is not None and color_source_vector is not None:
+        _warn_missing_groups(groups, color_source_vector, col_for_color)
+
     # When groups are specified, zero out non-matching label IDs so they render as background.
     # Only show non-matching labels if the user explicitly sets na_color.
     _na = render_params.cmap_params.na_color
@@ -1333,7 +1347,6 @@ def _render_labels(
         and color_source_vector is not None
         and (_na.default_color_set or _na.alpha == "00")
     ):
-        _warn_missing_groups(groups, color_source_vector, col_for_color)
         keep_vec = color_source_vector.isin(groups)
         matching_ids = instance_id[keep_vec]
         keep_mask = np.isin(label.values, matching_ids)

tests/pl/test_render_labels.py

@@ -12,6 +12,7 @@
 from spatialdata.models import Labels2DModel, TableModel
 
 import spatialdata_plot  # noqa: F401
+from spatialdata_plot._logging import logger, logger_warns
 from tests.conftest import DPI, PlotTester, PlotTesterMeta, _viridis_with_under_over, get_standard_RNG
 
 sc.pl.set_rcParams_defaults()
@@ -428,3 +429,21 @@ def test_raises_when_table_does_not_annotate_element(sdata_blobs: SpatialData):
             color="channel_0_sum",
             table_name="other_table",
         ).pl.show()
+
+
+def test_groups_warns_when_no_groups_match_labels(sdata_blobs: SpatialData, caplog):
+    """Warning fires when no groups match label color categories."""
+    labels_name = "blobs_labels"
+    instances = get_element_instances(sdata_blobs[labels_name])
+    n_obs = len(instances)
+    adata = AnnData(np.zeros((n_obs, 1)))
+    adata.obs["instance_id"] = instances.values
+    adata.obs["cat"] = pd.Categorical(["a", "b"] * (n_obs // 2) + ["a"] * (n_obs % 2))
+    adata.obs["region"] = labels_name
+    sdata_blobs["label_table"] = TableModel.parse(
+        adata=adata, region_key="region", instance_key="instance_id", region=labels_name
+    )
+    with logger_warns(caplog, logger, match="None of the requested groups"):
+        sdata_blobs.pl.render_labels(
+            labels_name, color="cat", groups=["nonexistent"], table_name="label_table", na_color=None
+        ).pl.show()

tests/pl/test_render_points.py

@@ -608,21 +608,23 @@ def test_groups_na_color_none_no_match_points(sdata_blobs: SpatialData):
     ).pl.show()
 
 
-def test_groups_warns_when_no_groups_match_points(sdata_blobs: SpatialData, caplog):
-    """When none of the groups match color categories, a warning should be emitted."""
+@pytest.mark.parametrize("na_color", [None, "red"])
+def test_groups_warns_when_no_groups_match_points(sdata_blobs: SpatialData, caplog, na_color):
+    """Warning fires regardless of na_color when no groups match."""
     sdata_blobs["blobs_points"]["cat_color"] = pd.Series(["a", "b", "c", "a"] * 50, dtype="category")
     with logger_warns(caplog, logger, match="None of the requested groups"):
         sdata_blobs.pl.render_points(
-            "blobs_points", color="cat_color", groups=["nonexistent"], na_color=None, size=30
+            "blobs_points", color="cat_color", groups=["nonexistent"], na_color=na_color, size=30
         ).pl.show()
 
 
-def test_groups_warns_when_some_groups_missing_points(sdata_blobs: SpatialData, caplog):
-    """When some groups match but others don't, a warning should list the missing ones."""
+@pytest.mark.parametrize("na_color", [None, "red"])
+def test_groups_warns_when_some_groups_missing_points(sdata_blobs: SpatialData, caplog, na_color):
+    """Warning fires regardless of na_color when some groups are missing."""
     sdata_blobs["blobs_points"]["cat_color"] = pd.Series(["a", "b", "c", "a"] * 50, dtype="category")
-    with logger_warns(caplog, logger, match="were not found in column"):
+    with logger_warns(caplog, logger, match="were not found in"):
         sdata_blobs.pl.render_points(
-            "blobs_points", color="cat_color", groups=["a", "nonexistent"], na_color=None, size=30
+            "blobs_points", color="cat_color", groups=["a", "nonexistent"], na_color=na_color, size=30
         ).pl.show()
 
 

tests/pl/test_render_shapes.py

@@ -1016,21 +1016,23 @@ def test_groups_na_color_none_no_match_shapes(sdata_blobs: SpatialData):
     sdata_blobs.pl.render_shapes("blobs_polygons", color="cat_color", groups=["nonexistent"], na_color=None).pl.show()
 
 
-def test_groups_warns_when_no_groups_match(sdata_blobs: SpatialData, caplog):
-    """When none of the groups match color categories, a warning should be emitted."""
+@pytest.mark.parametrize("na_color", [None, "red"])
+def test_groups_warns_when_no_groups_match(sdata_blobs: SpatialData, caplog, na_color):
+    """Warning fires regardless of na_color when no groups match."""
     sdata_blobs["blobs_polygons"]["cat_color"] = pd.Series(["a", "b", "a", "b", "a"], dtype="category")
     with logger_warns(caplog, logger, match="None of the requested groups"):
         sdata_blobs.pl.render_shapes(
-            "blobs_polygons", color="cat_color", groups=["nonexistent"], na_color=None
+            "blobs_polygons", color="cat_color", groups=["nonexistent"], na_color=na_color
         ).pl.show()
 
 
-def test_groups_warns_when_some_groups_missing(sdata_blobs: SpatialData, caplog):
-    """When some groups match but others don't, a warning should list the missing ones."""
+@pytest.mark.parametrize("na_color", [None, "red"])
+def test_groups_warns_when_some_groups_missing(sdata_blobs: SpatialData, caplog, na_color):
+    """Warning fires regardless of na_color when some groups are missing."""
     sdata_blobs["blobs_polygons"]["cat_color"] = pd.Series(["a", "b", "a", "b", "a"], dtype="category")
-    with logger_warns(caplog, logger, match="were not found in column"):
+    with logger_warns(caplog, logger, match="were not found in"):
         sdata_blobs.pl.render_shapes(
-            "blobs_polygons", color="cat_color", groups=["a", "nonexistent"], na_color=None
+            "blobs_polygons", color="cat_color", groups=["a", "nonexistent"], na_color=na_color
         ).pl.show()