Fix datashader single-group bug, make tests 2-panel comparisons

Fix: the datashader shapes path skipped categorical aggregation when
groups had exactly 1 entry (len(groups) > 1 was False), producing an
empty plot. Remove the erroneous groups-length guard.

Tests: all 4 groups-filtering PlotTester tests now show 2 panels
side-by-side (left: default with na_color shown, right: na_color=None
with filtered elements) for easy visual comparison.

Baseline images removed — will be regenerated by CI.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: timtreis

src/spatialdata_plot/pl/render.py

@@ -416,7 +416,7 @@ def _render_shapes(
 
         aggregate_with_reduction = None
         continuous_nan_shapes = None
-        if col_for_color is not None and (render_params.groups is None or len(render_params.groups) > 1):
+        if col_for_color is not None:
             if color_by_categorical:
                 # add a sentinel category so that shapes with NaN value are colored in the na_color
                 transformed_element[col_for_color] = _inject_ds_nan_sentinel(transformed_element[col_for_color])

tests/_images/Points_groups_na_color_none_filters_points.png

@@ -579,14 +579,24 @@ def test_plot_can_annotate_points_with_nan_in_df_continuous_datashader(self, sda
     def test_plot_groups_na_color_none_filters_points(self, sdata_blobs: SpatialData):
         """When groups is set and na_color=None, non-matching points are filtered out entirely."""
         sdata_blobs["blobs_points"]["cat_color"] = pd.Series(["a", "b", "c", "a"] * 50, dtype="category")
-        sdata_blobs.pl.render_points("blobs_points", color="cat_color", groups=["a"], na_color=None, size=30).pl.show()
+        _, axs = plt.subplots(nrows=1, ncols=2, layout="tight")
+        sdata_blobs.pl.render_points("blobs_points", color="cat_color", groups=["a"], size=30).pl.show(
+            ax=axs[0], title="default"
+        )
+        sdata_blobs.pl.render_points("blobs_points", color="cat_color", groups=["a"], na_color=None, size=30).pl.show(
+            ax=axs[1], title="na_color=None"
+        )
 
     def test_plot_groups_na_color_none_filters_points_datashader(self, sdata_blobs: SpatialData):
         """Groups filtering with na_color=None via datashader backend."""
         sdata_blobs["blobs_points"]["cat_color"] = pd.Series(["a", "b", "c", "a"] * 50, dtype="category")
+        _, axs = plt.subplots(nrows=1, ncols=2, layout="tight")
+        sdata_blobs.pl.render_points(
+            "blobs_points", color="cat_color", groups=["a"], size=30, method="datashader"
+        ).pl.show(ax=axs[0], title="default")
         sdata_blobs.pl.render_points(
             "blobs_points", color="cat_color", groups=["a"], na_color=None, size=30, method="datashader"
-        ).pl.show()
+        ).pl.show(ax=axs[1], title="na_color=None")
 
 
 def test_groups_na_color_none_no_match_points(sdata_blobs: SpatialData):

tests/_images/Points_groups_na_color_none_filters_points_datashader.png

@@ -986,14 +986,24 @@ def test_plot_can_annotate_shapes_with_nan_in_df_continuous_datashader(self, sda
     def test_plot_groups_na_color_none_filters_shapes(self, sdata_blobs: SpatialData):
         """When groups is set and na_color=None, non-matching shapes are filtered out entirely."""
         sdata_blobs["blobs_polygons"]["cat_color"] = pd.Series(["a", "b", "a", "b", "a"], dtype="category")
-        sdata_blobs.pl.render_shapes("blobs_polygons", color="cat_color", groups=["a"], na_color=None).pl.show()
+        _, axs = plt.subplots(nrows=1, ncols=2, layout="tight")
+        sdata_blobs.pl.render_shapes("blobs_polygons", color="cat_color", groups=["a"]).pl.show(
+            ax=axs[0], title="default"
+        )
+        sdata_blobs.pl.render_shapes("blobs_polygons", color="cat_color", groups=["a"], na_color=None).pl.show(
+            ax=axs[1], title="na_color=None"
+        )
 
     def test_plot_groups_na_color_none_filters_shapes_datashader(self, sdata_blobs: SpatialData):
         """Groups filtering with na_color=None via datashader backend."""
         sdata_blobs["blobs_polygons"]["cat_color"] = pd.Series(["a", "b", "a", "b", "a"], dtype="category")
+        _, axs = plt.subplots(nrows=1, ncols=2, layout="tight")
+        sdata_blobs.pl.render_shapes("blobs_polygons", color="cat_color", groups=["a"], method="datashader").pl.show(
+            ax=axs[0], title="default"
+        )
         sdata_blobs.pl.render_shapes(
             "blobs_polygons", color="cat_color", groups=["a"], na_color=None, method="datashader"
-        ).pl.show()
+        ).pl.show(ax=axs[1], title="na_color=None")
 
 
 def test_groups_na_color_none_no_match_shapes(sdata_blobs: SpatialData):