Fix render_points datashader pipeline: dead code, silent failures, and fragile alignment

- Forward `default_reduction` to aggregation instead of ignoring it (_datashader.py)
- Warn when `ds_reduction` is set for categorical data (always uses count)
- Warn when `groups` is set with continuous color column (silently ignored)
- Warn on color_vector/cat_series length mismatch in `_build_datashader_color_key`
- Only set cmap fallback in `_ds_shade_categorical` when no color_key is present
- Add 54 unit tests covering all fixes and datashader reduction behavior

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

Author: timtreis

src/spatialdata_plot/pl/_datashader.py

@@ -62,6 +62,11 @@ def _build_datashader_color_key(
     """Build a datashader ``color_key`` dict from a categorical series and its color vector."""
     na_hex = _hex_no_alpha(na_color_hex) if na_color_hex.startswith("#") else na_color_hex
     colors_arr = np.asarray(color_vector, dtype=object)
+    if len(colors_arr) != len(cat_series.codes):
+        logger.warning(
+            f"color_vector length ({len(colors_arr)}) does not match categorical series length "
+            f"({len(cat_series.codes)}); some categories may receive the na_color fallback."
+        )
     first_color: dict[str, str] = {}
     for code, color in zip(cat_series.codes, colors_arr, strict=False):
         if code < 0:
@@ -119,6 +124,11 @@ def _agg_call(element: Any, agg_func: Any) -> Any:
 
     if col_for_color is not None:
         if color_by_categorical:
+            if ds_reduction is not None:
+                logger.warning(
+                    f'ds_reduction="{ds_reduction}" is ignored for categorical data; '
+                    "categorical aggregation always uses count."
+                )
             transformed_element[col_for_color] = _inject_ds_nan_sentinel(transformed_element[col_for_color])
             agg = _agg_call(transformed_element, ds.by(col_for_color, ds.count()))
         else:
@@ -127,7 +137,9 @@ def _agg_call(element: Any, agg_func: Any) -> Any:
                 f'Using the datashader reduction "{reduction_name}". "max" will give an output '
                 "very close to the matplotlib result."
             )
-            agg = _datashader_aggregate_with_function(ds_reduction, cvs, transformed_element, col_for_color, geom_type)
+            agg = _datashader_aggregate_with_function(
+                reduction_name, cvs, transformed_element, col_for_color, geom_type
+            )
             reduction_bounds = (agg.min(), agg.max())
 
             nan_elements = transformed_element[transformed_element[col_for_color].isnull()]
@@ -244,7 +256,7 @@ def _ds_shade_categorical(
 ) -> Any:
     """Shade a categorical or no-color datashader aggregate."""
     ds_cmap = None
-    if color_vector is not None:
+    if color_key is None and color_vector is not None:
         ds_cmap = color_vector[0]
         if isinstance(ds_cmap, str) and ds_cmap[0] == "#":
             ds_cmap = _hex_no_alpha(ds_cmap)

src/spatialdata_plot/pl/render.py

@@ -108,6 +108,20 @@ def _reparse_points(
     )
 
 
+def _warn_groups_ignored_continuous(
+    groups: str | list[str] | None,
+    color_source_vector: pd.Categorical | None,
+    col_for_color: str | None,
+) -> None:
+    """Warn when ``groups`` is set but coloring is continuous (no categorical source)."""
+    if groups is not None and color_source_vector is None and col_for_color is not None:
+        logger.warning(
+            f"`groups` is ignored when coloring by continuous column '{col_for_color}'. "
+            "`groups` filters categories of the column specified via `color`; "
+            "it has no effect on continuous data."
+        )
+
+
 def _warn_missing_groups(
     groups: str | list[str],
     color_source_vector: pd.Categorical,
@@ -329,6 +343,8 @@ def _render_shapes(
 
     values_are_categorical = color_source_vector is not None
 
+    _warn_groups_ignored_continuous(groups, color_source_vector, col_for_color)
+
     if groups is not None and color_source_vector is not None:
         _warn_missing_groups(groups, color_source_vector, col_for_color)
 
@@ -784,6 +800,8 @@ 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)
 
+    _warn_groups_ignored_continuous(groups, color_source_vector, col_for_color)
+
     if groups is not None and color_source_vector is not None:
         _warn_missing_groups(groups, color_source_vector, col_for_color)
 
@@ -1335,6 +1353,8 @@ def _render_labels(
         else:
             assert color_source_vector is None
 
+    _warn_groups_ignored_continuous(groups, color_source_vector, col_for_color)
+
     if groups is not None and color_source_vector is not None:
         _warn_missing_groups(groups, color_source_vector, col_for_color)