Handle matching coordinates and dimensions with differing shapes

kerchunk/netCDF3.py

@@ -156,10 +156,10 @@ def translate(self):
         out = self.out
         z = zarr.open(out, mode="w")
         for dim, var in self.variables.items():
-            if dim in self.dimensions:
-                shape = self.dimensions[dim]
-            elif dim in self.chunks:
+            if dim in self.chunks:
                 shape = self.chunks[dim][-1]
+            elif dim in self.dimensions:
+                shape = self.dimensions[dim]
             else:
                 # defer record array
                 continue

kerchunk/tests/test_netcdf.py

@@ -1,12 +1,18 @@
 import os
 
+
 import fsspec
 import numpy as np
+from packaging.version import Version
 import pytest
 from kerchunk import netCDF3
 
 xr = pytest.importorskip("xarray")
 
+
+has_xarray_2023_8_0 = Version(xr.__version__) >= Version("2023.8.0")
+
+
 arr = np.random.rand(1, 10, 10)
 static = xr.DataArray(data=np.random.rand(10, 10), dims=["x", "y"], name="static")
 data = xr.DataArray(
@@ -89,3 +95,46 @@ def test_unlimited(unlimited_dataset):
     assert (ds.lat.values == expected.lat.values).all()
     assert (ds.lon.values == expected.lon.values).all()
     assert (ds.temp.values == expected.temp.values).all()
+
+
+@pytest.fixture()
+def matching_coordinate_dimension_dataset(tmpdir):
+    """Create a dataset with a coordinate dimension that matches the name of a
+    variable dimension."""
+    # https://unidata.github.io/netcdf4-python/#creatingopeningclosing-a-netcdf-file
+    from netCDF4 import Dataset
+
+    fn = os.path.join(tmpdir, "test.nc")
+    rootgrp = Dataset(fn, "w", format="NETCDF3_64BIT")
+    rootgrp.createDimension("node", 2)
+    rootgrp.createDimension("sigma", 2)
+
+    node = rootgrp.createVariable("node", "i4", ("node",))
+    sigma = rootgrp.createVariable("sigma", "f8", ("sigma", "node"))
+
+    node[:] = [0, 1]
+    for i in range(2):
+        sigma[i] = np.random.uniform(size=(2,))
+
+    rootgrp.close()
+    return fn
+
+
+@pytest.mark.skipif(
+    not has_xarray_2023_8_0, reason="XArray 2023.08.0 is required for this behavior."
+)
+def test_matching_coordinate_dimension(matching_coordinate_dimension_dataset):
+    fn = matching_coordinate_dimension_dataset
+    expected = xr.open_dataset(fn, engine="scipy")
+    h = netCDF3.NetCDF3ToZarr(fn)
+    out = h.translate()
+    ds = xr.open_dataset(
+        "reference://",
+        engine="zarr",
+        backend_kwargs={
+            "consolidated": False,
+            "storage_options": {"fo": out},
+        },
+    )
+    assert (ds.node.values == expected.node.values).all()
+    assert (ds.sigma.values == expected.sigma.values).all()