Support grid_topology, mesh_topology CF roles. (#420)

Author: dcherian

cf_xarray/criteria.py

@@ -9,7 +9,17 @@
 from typing import Mapping, MutableMapping, Tuple
 
 cf_role_criteria: Mapping[str, Mapping[str, str]] = {
-    k: {"cf_role": k} for k in ("timeseries_id", "profile_id", "trajectory_id")
+    k: {"cf_role": k}
+    for k in (
+        # CF Discrete sampling geometry
+        "timeseries_id",
+        "profile_id",
+        "trajectory_id",
+        # SGRID
+        "grid_topology",
+        # UGRID
+        "mesh_topology",
+    )
 }
 
 coordinate_criteria: MutableMapping[str, MutableMapping[str, Tuple]] = {

cf_xarray/tests/test_accessor.py

@@ -1766,6 +1766,18 @@ def test_cf_role() -> None:
     dsg.foo.cf.plot(x="trajectory_id")
 
 
+def test_grid_topology() -> None:
+    ds = xr.Dataset(
+        data_vars={},
+        coords={
+            "mesh": (tuple(), 1, {"cf_role": "mesh_topology"}),
+            "grid": (tuple(), 1, {"cf_role": "grid_topology"}),
+        },
+    )
+    assert_identical(ds.cf["grid_topology"], ds.grid.reset_coords(drop=True))
+    assert_identical(ds.cf["mesh_topology"], ds.mesh.reset_coords(drop=True))
+
+
 @requires_scipy
 def test_curvefit() -> None:
     from cf_xarray.datasets import airds

doc/index.rst

@@ -53,6 +53,7 @@ or using ``conda``
    bounds
    coding
    dsg
+   sgrid_ugrid
    geometry
    plotting
    custom-criteria

doc/sgrid_ugrid.md

@@ -0,0 +1,5 @@
+# SGRID / UGRID
+
+`cf_xarray` support identifying either the `mesh_topology` (UGRID) or `grid_topology` (SGRID) variables using the `cf_role` attribute.
+
+Further support for interpreting the SGRID and UGRID conventions can be added. Contributions are welcome!