Identify non dimension coords

docs/releases.rst

@@ -29,6 +29,8 @@ Bug fixes
   By `Tom Nicholas <https://github.com/TomNicholas>`_.
 - Ensure that `.attrs` on coordinate variables are preserved during round-tripping. (:issue:`155`, :pull:`154`)
   By `Tom Nicholas <https://github.com/TomNicholas>`_.
+- Ensure that non-dimension coordinate variables described via the CF conventions are preserved during round-tripping. (:issue:`105`, :pull:`156`)
+  By `Tom Nicholas <https://github.com/TomNicholas>`_.
 
 Documentation
 ~~~~~~~~~~~~~

virtualizarr/kerchunk.py

@@ -217,11 +217,18 @@ def dataset_to_kerchunk_refs(ds: xr.Dataset) -> KerchunkStoreRefs:
 
         all_arr_refs.update(prepended_with_var_name)
 
+    zattrs = ds.attrs
+    if ds.coords:
+        coord_names = list(ds.coords)
+        # this weird concatenated string instead of a list of strings is inconsistent with how other features in the kerchunk references format are stored
+        # see https://github.com/zarr-developers/VirtualiZarr/issues/105#issuecomment-2187266739
+        zattrs["coordinates"] = " ".join(coord_names)
+
     ds_refs = {
         "version": 1,
         "refs": {
             ".zgroup": '{"zarr_format":2}',
-            ".zattrs": ujson.dumps(ds.attrs),
+            ".zattrs": ujson.dumps(zattrs),
             **all_arr_refs,
         },
     }

virtualizarr/tests/test_integration.py

@@ -1,3 +1,4 @@
+import numpy as np
 import pytest
 import xarray as xr
 import xarray.testing as xrt
@@ -95,6 +96,31 @@ def test_kerchunk_roundtrip_concat(self, tmpdir, format):
         # assert identical to original dataset
         xrt.assert_identical(roundtrip, ds)
 
+    def test_non_dimension_coordinates(self, tmpdir, format):
+        # regression test for GH issue #105
+
+        # set up example xarray dataset containing non-dimension coordinate variables
+        ds = xr.Dataset(coords={"lat": (["x", "y"], np.arange(6).reshape(2, 3))})
+
+        # save it to disk as netCDF (in temporary directory)
+        ds.to_netcdf(f"{tmpdir}/non_dim_coords.nc")
+
+        vds = open_virtual_dataset(f"{tmpdir}/non_dim_coords.nc", indexes={})
+
+        assert "lat" in vds.coords
+        assert "coordinates" not in vds.attrs
+
+        # write those references to disk as kerchunk references format
+        vds.virtualize.to_kerchunk(f"{tmpdir}/refs.{format}", format=format)
+
+        # use fsspec to read the dataset from disk via the kerchunk references
+        roundtrip = xr.open_dataset(
+            f"{tmpdir}/refs.{format}", engine="kerchunk", decode_times=False
+        )
+
+        # assert equal to original dataset
+        xrt.assert_identical(roundtrip, ds)
+
 
 def test_open_scalar_variable(tmpdir):
     # regression test for GH issue #100

virtualizarr/xarray.py

@@ -117,6 +117,7 @@ def open_virtual_dataset(
             virtual_array_class=virtual_array_class,
         )
         ds_attrs = kerchunk.fully_decode_arr_refs(vds_refs["refs"]).get(".zattrs", {})
+        coord_names = ds_attrs.pop("coordinates", [])
 
         if indexes is None or len(loadable_variables) > 0:
             # TODO we are reading a bunch of stuff we know we won't need here, e.g. all of the data variables...
@@ -152,7 +153,7 @@ def open_virtual_dataset(
 
         vars = {**virtual_vars, **loadable_vars}
 
-        data_vars, coords = separate_coords(vars, indexes)
+        data_vars, coords = separate_coords(vars, indexes, coord_names)
 
         vds = xr.Dataset(
             data_vars,
@@ -177,6 +178,7 @@ def open_virtual_dataset_from_v3_store(
     _storepath = Path(storepath)
 
     ds_attrs = attrs_from_zarr_group_json(_storepath / "zarr.json")
+    coord_names = ds_attrs.pop("coordinates", [])
 
     # TODO recursive glob to create a datatree
     # Note: this .is_file() check should not be necessary according to the pathlib docs, but tests fail on github CI without it
@@ -205,7 +207,7 @@ def open_virtual_dataset_from_v3_store(
     else:
         indexes = dict(**indexes)  # for type hinting: to allow mutation
 
-    data_vars, coords = separate_coords(vars, indexes)
+    data_vars, coords = separate_coords(vars, indexes, coord_names)
 
     ds = xr.Dataset(
         data_vars,
@@ -223,8 +225,10 @@ def virtual_vars_from_kerchunk_refs(
     virtual_array_class=ManifestArray,
 ) -> Mapping[str, xr.Variable]:
     """
-    Translate a store-level kerchunk reference dict into aa set of xarray Variables containing virtualized arrays.
+    Translate a store-level kerchunk reference dict into aaset of xarray Variables containing virtualized arrays.
 
+    Parameters
+    ----------
     drop_variables: list[str], default is None
         Variables in the file to drop before returning.
     virtual_array_class
@@ -263,12 +267,12 @@ def dataset_from_kerchunk_refs(
     """
 
     vars = virtual_vars_from_kerchunk_refs(refs, drop_variables, virtual_array_class)
+    ds_attrs = kerchunk.fully_decode_arr_refs(refs["refs"]).get(".zattrs", {})
+    coord_names = ds_attrs.pop("coordinates", [])
 
     if indexes is None:
         indexes = {}
-    data_vars, coords = separate_coords(vars, indexes)
-
-    ds_attrs = kerchunk.fully_decode_arr_refs(refs["refs"]).get(".zattrs", {})
+    data_vars, coords = separate_coords(vars, indexes, coord_names)
 
     vds = xr.Dataset(
         data_vars,
@@ -301,6 +305,7 @@ def variable_from_kerchunk_refs(
 def separate_coords(
     vars: Mapping[str, xr.Variable],
     indexes: MutableMapping[str, Index],
+    coord_names: Iterable[str] | None = None,
 ) -> tuple[Mapping[str, xr.Variable], xr.Coordinates]:
     """
     Try to generate a set of coordinates that won't cause xarray to automatically build a pandas.Index for the 1D coordinates.
@@ -310,8 +315,8 @@ def separate_coords(
     Will also preserve any loaded variables and indexes it is passed.
     """
 
-    # this would normally come from CF decoding, let's hope the fact we're skipping that doesn't cause any problems...
-    coord_names: list[str] = []
+    if coord_names is None:
+        coord_names = []
 
     # split data and coordinate variables (promote dimension coordinates)
     data_vars = {}