edits

Author: dcherian

xarray/core/dataset.py

@@ -2481,11 +2481,11 @@ def chunk(
                 f"chunks keys {tuple(bad_dims)} not found in data dimensions {tuple(self.sizes.keys())}"
             )
 
-        def _resolve_frequency(name: Hashable, resampler: Resampler) -> tuple[int, ...]:
+        def _resolve_resampler(name: Hashable, resampler: Resampler) -> tuple[int, ...]:
             variable = self._variables.get(name, None)
             if variable is None:
                 raise ValueError(
-                    f"Cannot chunk by resampler {resampler!r} for virtual variables."
+                    f"Cannot chunk by resampler {resampler!r} for virtual variable {name!r}."
                 )
             if variable.ndim != 1:
                 raise ValueError(
@@ -2501,7 +2501,7 @@ def _resolve_frequency(name: Hashable, resampler: Resampler) -> tuple[int, ...]:
 
         chunks_mapping_ints: Mapping[Any, T_ChunkDim] = {
             name: (
-                _resolve_frequency(name, chunks)
+                _resolve_resampler(name, chunks)
                 if isinstance(chunks, Resampler)
                 else chunks
             )

xarray/tests/test_dataset.py

@@ -1135,15 +1135,6 @@ def test_chunks_does_not_load_data(self) -> None:
         ds = open_dataset(store)
         assert ds.chunks == {}
 
-    @requires_dask
-    def test_chunk(self) -> None:
-        data = create_test_data()
-        for chunks in [1, 2, 3, 4, 5]:
-            rechunked = data.chunk({"dim1": chunks})
-            assert rechunked.chunks["dim1"] == (chunks,) * (8 // chunks) + (
-                (8 % chunks,) if 8 % chunks else ()
-            )
-
     @requires_dask
     @pytest.mark.parametrize(
         "use_cftime,calendar",
@@ -1223,6 +1214,9 @@ def test_chunk_by_season_resampler_errors(self):
         # This should work
         result = ds.chunk(x=SeasonResampler(["DJF", "MAM", "JJA", "SON"]))
         assert result.chunks is not None
+
+    @requires_dask
+    def test_chunk(self) -> None:
         data = create_test_data()
         for v in data.variables.values():
             assert isinstance(v.data, np.ndarray)