fix(render_points): scope resolved norm to matplotlib, keep datashader autoscaling

d5a811a routed continuous points through _resolve_continuous_norm, but the
resolved norm was passed to BOTH backends. For datashader the displayed value is
the per-pixel aggregate (count/sum/reduction), whose range differs from the
per-point color vector — applying a color-vector-derived vmin/vmax mis-scaled the
colorbar and painted empty pixels (purple background) instead of leaving them
transparent.

Scope the resolved norm to the matplotlib backend (where each point is colored by
its own value); datashader keeps the un-scaled fresh_norm so _apply_ds_norm
autoscales to the aggregate (honoring any explicit vmin/vmax) — the pre-d5a811a
behavior. Reverts the datashader point baselines regenerated in error.

Author: timtreis

src/spatialdata_plot/pl/render.py

@@ -1415,15 +1415,6 @@ def _render_points(
 
     trans, trans_data = _prepare_transformation(sdata.points[element], coordinate_system, ax)
 
-    # Continuous points resolve their norm through the shared resolver so the fill and colorbar match
-    # the shapes/labels treatment (degenerate [0, 1] reset, LogNorm/PowerNorm preserved) instead of
-    # letting ax.scatter autoscale a fresh linear norm. Non-continuous keeps the un-scaled fresh norm.
-    norm = (
-        _resolve_continuous_norm(color_spec.color_vector, render_params.cmap_params)
-        if color_spec.is_continuous
-        else render_params.cmap_params.fresh_norm()
-    )
-
     method = render_params.method
 
     if render_params.density:
@@ -1435,6 +1426,11 @@ def _render_points(
     _default_reduction: _DsReduction = "sum"
 
     if method == "datashader":
+        # datashader colors the per-pixel AGGREGATE (count/sum/reduction), whose range differs from
+        # the per-point color vector. Pass an un-resolved norm so _apply_ds_norm autoscales to the
+        # aggregate (honoring any explicit vmin/vmax) — resolving from the color vector would mis-scale
+        # reductions and paint empty pixels.
+        norm = render_params.cmap_params.fresh_norm()
         _log_datashader_method(method, render_params.ds_reduction, _default_reduction)
 
         # Apply transformations and materialize to pandas immediately so
@@ -1471,6 +1467,14 @@ def _render_points(
         color_spec = color_spec.evolve(source_vector=csv, color_vector=cv)
 
     elif method == "matplotlib":
+        # matplotlib colors each point by its own value, so resolve the norm (degenerate [0, 1] reset,
+        # LogNorm/PowerNorm preserved) to match the shapes/labels treatment instead of letting
+        # ax.scatter autoscale a fresh linear norm. Non-continuous keeps the un-scaled fresh norm.
+        norm = (
+            _resolve_continuous_norm(color_spec.color_vector, render_params.cmap_params)
+            if color_spec.is_continuous
+            else render_params.cmap_params.fresh_norm()
+        )
         # update axis limits if plot was empty before (necessary if datashader comes after)
         update_parameters = not _mpl_ax_contains_elements(ax)
         cax = _scatter_points(