fix table name and add unit test for colors passed via .uns

src/spatialdata_plot/pl/utils.py

@@ -755,7 +755,7 @@ def _set_color_source_vec(
         color_source_vector = pd.Categorical(color_source_vector)  # convert, e.g., `pd.Series`
 
         color_mapping = _get_categorical_color_mapping(
-            adata=sdata.table,
+            adata=sdata.tables[table_name] if table_name is not None else sdata.table,
             cluster_key=value_to_plot,
             color_source_vector=color_source_vector,
             groups=groups,

tests/pl/test_render_labels.py

@@ -7,13 +7,12 @@
 import scanpy as sc
 from anndata import AnnData
 from spatial_image import to_spatial_image
-from spatialdata import SpatialData, deepcopy, get_element_instances
+from spatialdata import SpatialData, bounding_box_query, deepcopy, get_element_instances
 from spatialdata.models import TableModel
 
 import spatialdata_plot  # noqa: F401
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
 
-RNG = np.random.default_rng(seed=42)
 sc.pl.set_rcParams_defaults()
 sc.set_figure_params(dpi=DPI, color_map="viridis")
 matplotlib.use("agg")  # same as GitHub action runner
@@ -214,7 +213,63 @@ def test_plot_label_categorical_color(self, sdata_blobs: SpatialData):
         self._make_tablemodel_with_categorical_labels(sdata_blobs, labels_name="blobs_labels")
         sdata_blobs.pl.render_labels("blobs_labels", color="category").pl.show()
 
+    def test_plot_label_categorical_color_and_colors_in_uns(self, sdata_blobs: SpatialData):
+        self._make_tablemodel_with_categorical_labels(sdata_blobs, labels_name="blobs_labels")
+        # purple, green, yellow
+        sdata_blobs["other_table"].uns["category_colors"] = ["#800080", "#008000", "#FFFF00"]
+        # placeholder, otherwise "category_colors" will be ignored
+        sdata_blobs["other_table"].uns["category"] = "__value__"
+        sdata_blobs.pl.render_labels("blobs_labels", color="category").pl.show()
+
+    def test_plot_label_categorical_color_and_colors_in_uns_query_uns_colors_removed(self, sdata_blobs: SpatialData):
+        self._make_tablemodel_with_categorical_labels(sdata_blobs, labels_name="blobs_labels")
+        # purple, green, yellow
+        sdata_blobs["other_table"].uns["category_colors"] = ["#800080", "#008000", "#FFFF00"]
+        # placeholder, otherwise "category_colors" will be ignored
+        sdata_blobs["other_table"].uns["category"] = "__value__"
+        sdata_blobs = bounding_box_query(
+            sdata_blobs,
+            axes=("y", "x"),
+            min_coordinate=[0, 0],
+            max_coordinate=[100, 100],
+            target_coordinate_system="global",
+        )
+        # we would expect colors purple and yellow for a and c, but we see default colors blue and orange,
+        # Reason: "category_colors" is removed by `.filter_by_coordinate_system` in
+        # `spatialdata_plot.pl.render._render_labels`.
+        # Why? Because `.bounding_box_query` removes "category_colors" that are not in the query,
+        # but restores original number of catergories in `.obs["category"]`, see https://github.com/scverse/anndata/issues/997,
+        # leading to mismatch and removal of "category_colors" by `.filter_by_coordinate_system`.
+        assert all(sdata_blobs["other_table"].obs["category"].unique() == ["a", "c"])
+        assert all(sdata_blobs["other_table"].uns["category_colors"] == ["#800080", "#FFFF00"])
+        # but due to https://github.com/scverse/anndata/issues/997:
+        assert all(sdata_blobs["other_table"].obs["category"].cat.categories == ["a", "b", "c"])
+        sdata_blobs.pl.render_labels("blobs_labels", color="category").pl.show()
+
+    def test_plot_label_categorical_color_and_colors_in_uns_query_workaround(self, sdata_blobs: SpatialData):
+        self._make_tablemodel_with_categorical_labels(sdata_blobs, labels_name="blobs_labels")
+        # purple, green, yellow
+        sdata_blobs["other_table"].uns["category_colors"] = ["#800080", "#008000", "#FFFF00"]
+        # placeholder, otherwise "category_colors" will be ignored
+        sdata_blobs["other_table"].uns["category"] = "__value__"
+        sdata_blobs = bounding_box_query(
+            sdata_blobs,
+            axes=("y", "x"),
+            min_coordinate=[0, 0],
+            max_coordinate=[100, 100],
+            target_coordinate_system="global",
+        )
+        assert all(sdata_blobs["other_table"].obs["category"].unique() == ["a", "c"])
+        assert all(sdata_blobs["other_table"].uns["category_colors"] == ["#800080", "#FFFF00"])
+        # but due to https://github.com/scverse/anndata/issues/997:
+        assert all(sdata_blobs["other_table"].obs["category"].cat.categories == ["a", "b", "c"])
+        sdata_blobs["other_table"].obs["category"] = (
+            sdata_blobs["other_table"].obs["category"].cat.remove_unused_categories()
+        )
+        sdata_blobs.pl.render_labels("blobs_labels", color="category").pl.show()
+
     def _make_tablemodel_with_categorical_labels(self, sdata_blobs, labels_name: str):
+        RNG = np.random.default_rng(seed=42)
         instances = get_element_instances(sdata_blobs[labels_name])
         n_obs = len(instances)
         adata = AnnData(
@@ -235,5 +290,6 @@ def _make_tablemodel_with_categorical_labels(self, sdata_blobs, labels_name: str
         sdata_blobs["other_table"].obs["category"] = sdata_blobs["other_table"].obs["category"].astype("category")
 
     def test_plot_can_annotate_labels_with_table_layer(self, sdata_blobs: SpatialData):
+        RNG = np.random.default_rng(seed=42)
         sdata_blobs["table"].layers["normalized"] = RNG.random(sdata_blobs["table"].X.shape)
         sdata_blobs.pl.render_labels("blobs_labels", color="channel_0_sum", table_layer="normalized").pl.show()