generalized chunk_hint function inside indexing

xarray/core/indexing.py

@@ -17,6 +17,7 @@
 from xarray.core import duck_array_ops
 from xarray.core.nputils import NumpyVIndexAdapter
 from xarray.core.options import OPTIONS
+from xarray.core.parallelcompat import get_chunked_array_type, is_chunked_array
 from xarray.core.pycompat import array_type, integer_types, is_duck_dask_array
 from xarray.core.types import T_Xarray
 from xarray.core.utils import (
@@ -1075,16 +1076,15 @@ def _arrayize_vectorized_indexer(indexer, shape):
     return VectorizedIndexer(tuple(new_key))
 
 
-def _dask_array_with_chunks_hint(array, chunks):
-    """Create a dask array using the chunks hint for dimensions of size > 1."""
-    import dask.array as da
+def _chunked_array_with_chunks_hint(array, chunks, chunkmanager):
+    """Create a chunked array using the chunks hint for dimensions of size > 1."""
 
     if len(chunks) < array.ndim:
         raise ValueError("not enough chunks in hint")
     new_chunks = []
     for chunk, size in zip(chunks, array.shape):
         new_chunks.append(chunk if size > 1 else (1,))
-    return da.from_array(array, new_chunks)
+    return chunkmanager.from_array(array, new_chunks)
 
 
 def _logical_any(args):
@@ -1098,8 +1098,11 @@ def _masked_result_drop_slice(key, data=None):
     new_keys = []
     for k in key:
         if isinstance(k, np.ndarray):
-            if is_duck_dask_array(data):
-                new_keys.append(_dask_array_with_chunks_hint(k, chunks_hint))
+            if is_chunked_array(data):
+                chunkmanager = get_chunked_array_type(data)
+                new_keys.append(
+                    _chunked_array_with_chunks_hint(k, chunks_hint, chunkmanager)
+                )
             elif isinstance(data, array_type("sparse")):
                 import sparse
 

xarray/core/parallelcompat.py

@@ -9,7 +9,7 @@
 
 import numpy as np
 
-from xarray.core import indexing, utils
+from xarray.core import utils
 from xarray.core.pycompat import DuckArrayModule, is_chunked_array, is_duck_dask_array
 from xarray.core.types import T_Chunks
 
@@ -197,6 +197,8 @@ def chunks(self, data: T_DaskArray) -> T_Chunks:
     def from_array(self, data: np.ndarray, chunks, **kwargs) -> T_DaskArray:
         import dask.array as da
 
+        from xarray.core import indexing
+
         # dask-specific kwargs
         name = kwargs.pop("name", None)
         lock = kwargs.pop("lock", False)