fix(show): render all coordinate systems for type-distributed elements

src/spatialdata_plot/pl/basic.py

@@ -1673,7 +1673,10 @@ def _resolve_coordinate_systems(
         if cs not in sdata.coordinate_systems:
             raise ValueError(f"Unknown coordinate system '{cs}', valid choices are: {sdata.coordinate_systems}")
 
-    elements_to_be_rendered = _get_elements_to_be_rendered(render_cmds, cs_index, cs)
+    # Union elements across all coordinate systems, not just the last one validated above.
+    elements_to_be_rendered = list(
+        dict.fromkeys(e for cs in coordinate_systems for e in _get_elements_to_be_rendered(render_cmds, cs_index, cs))
+    )
 
     # filter out cs without relevant elements
     cmds = [cmd for cmd, _ in render_cmds]

tests/pl/test_utils.py

@@ -791,3 +791,26 @@ def test_missing_instances_become_nan(self):
         new = _extract_color_column(sdata["table"], "g0", origin="var", element=sdata["shapes"], element_name="shapes")
         assert len(new) == 30
         assert int(new.isna().sum()) == 5
+
+
+def test_show_renders_all_coordinate_systems_for_distributed_elements():
+    """Regression for #694: element types split across coordinate systems must all render.
+
+    Before the fix, ``_resolve_coordinate_systems`` computed the rendered element set from a
+    leaked loop variable (the last validated CS only), so ``_get_valid_cs`` could drop a CS whose
+    elements lived elsewhere. ``_get_elements_to_be_rendered`` keys on element *type*, so the bug
+    only surfaces when the leftover CS lacks a queued element type: here the image lives in ``cs_a``
+    and the labels in ``cs_b``, so the leaked ``cs_b`` (no image) used to drop ``cs_a``.
+    """
+    from spatialdata.models import Image2DModel
+    from spatialdata.transformations import Identity
+
+    rng = np.random.default_rng(0)
+    img = Image2DModel.parse(rng.random((3, 16, 16)), transformations={"cs_a": Identity()})
+    lab = Labels2DModel.parse(rng.integers(0, 5, (16, 16)), transformations={"cs_b": Identity()})
+    sdata = SpatialData(images={"img": img}, labels={"lab": lab})
+
+    axes = sdata.pl.render_images("img").pl.render_labels("lab").pl.show(return_ax=True)
+    axes = axes if isinstance(axes, list) else [axes]
+    assert {ax.get_title() for ax in axes} == {"cs_a", "cs_b"}
+    plt.close("all")