add h5netcdf+dask tests

xarray/tests/test_backends.py

@@ -1916,6 +1916,46 @@ def test_dump_encodings_h5py(self):
             assert actual.x.encoding['compression_opts'] is None
 
 
+@requires_h5netcdf
+@requires_dask
+@pytest.mark.filterwarnings('ignore:deallocating CachingFileManager')
+class TestH5NetCDFViaDaskData(TestH5NetCDFData):
+
+    @contextlib.contextmanager
+    def roundtrip(self, data, save_kwargs={}, open_kwargs={},
+                  allow_cleanup_failure=False):
+        with TestH5NetCDFData.roundtrip(
+                self, data, save_kwargs, open_kwargs,
+                allow_cleanup_failure) as ds:
+            yield ds.chunk()
+
+    def test_dataset_caching(self):
+        # caching behavior differs for dask
+        pass
+
+    @pytest.mark.xfail(reason="Failing to round trip unlimited dims")
+    def test_encoding_unlimited_dims(self):
+        # TODO: this should pass
+        super(TestH5NetCDFViaDaskData, self).test_encoding_unlimited_dims()
+
+    def test_write_inconsistent_chunks(self):
+        # Construct two variables with the same dimensions, but different
+        # chunk sizes.
+        x = da.zeros((100, 100), dtype='f4', chunks=(50, 100))
+        x = DataArray(data=x, dims=('lat', 'lon'), name='x')
+        x.encoding['chunksizes'] = (50, 100)
+        x.encoding['original_shape'] = (100, 100)
+        y = da.ones((100, 100), dtype='f4', chunks=(100, 50))
+        y = DataArray(data=y, dims=('lat', 'lon'), name='y')
+        y.encoding['chunksizes'] = (100, 50)
+        y.encoding['original_shape'] = (100, 100)
+        # Put them both into the same dataset
+        ds = Dataset({'x': x, 'y': y})
+        with self.roundtrip(ds) as actual:
+            assert actual['x'].encoding['chunksizes'] == (50, 100)
+            assert actual['y'].encoding['chunksizes'] == (100, 50)
+
+
 @pytest.fixture(params=['scipy', 'netcdf4', 'h5netcdf', 'pynio'])
 def readengine(request):
     return request.param