Fix empty indexing (#10870)

* fix indexing with empty arrays for OUTER_1VECTOR
* add test
* add whats-new.rst entry
---------
Co-authored-by: Deepak Cherian <[email protected]>

Author: kmuehlbauer

doc/whats-new.rst

@@ -32,12 +32,13 @@ Bug Fixes
 ~~~~~~~~~
 - Fix h5netcdf backend for format=None, use same rule as netcdf4 backend (:pull:`10859`).
   By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_
-
 - ``netcdf4`` and ``pydap`` backends now use stricter URL detection to avoid incorrectly claiming
   remote URLs. The ``pydap`` backend now only claims URLs with explicit DAP protocol indicators
   (``dap2://`` or ``dap4://`` schemes, or ``/dap2/`` or ``/dap4/`` in the URL path). This prevents
   both backends from claiming remote Zarr stores and other non-DAP URLs without an explicit
   ``engine=`` argument. (:pull:`10804`). By `Ian Hunt-Isaak <https://github.com/ianhi>`_.
+- Fix indexing with empty arrays for scipy & h5netcdf backends which now resolves to empty slices (:issue:`10867`, :pull:`10870`).
+  By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_
 
 Documentation
 ~~~~~~~~~~~~~

xarray/core/indexing.py

@@ -1366,15 +1366,19 @@ def _decompose_outer_indexer(
         gains = [
             (
                 (np.max(k) - np.min(k) + 1.0) / len(np.unique(k))
-                if isinstance(k, np.ndarray)
+                if isinstance(k, np.ndarray) and k.size != 0
                 else 0
             )
             for k in indexer_elems
         ]
         array_index = np.argmax(np.array(gains)) if len(gains) > 0 else None
 
         for i, (k, s) in enumerate(zip(indexer_elems, shape, strict=False)):
-            if isinstance(k, np.ndarray) and i != array_index:
+            if isinstance(k, np.ndarray) and k.size == 0:
+                # empty np.ndarray key is converted to empty slice
+                # see https://github.com/pydata/xarray/issues/10867
+                backend_indexer.append(slice(0, 0))
+            elif isinstance(k, np.ndarray) and i != array_index:
                 # np.ndarray key is converted to slice that covers the entire
                 # entries of this key.
                 backend_indexer.append(slice(np.min(k), np.max(k) + 1))

xarray/tests/test_backends.py

@@ -986,6 +986,15 @@ def test_isel_dataarray(self) -> None:
             actual = on_disk.isel(dim2=on_disk["dim2"] < 3)
             assert_identical(expected, actual)
 
+    def test_empty_isel(self) -> None:
+        # Make sure isel works lazily with empty indexer.
+        # GH:issue:10867
+        in_memory = xr.Dataset({"a": ("x", np.arange(4))}, coords={"x": np.arange(4)})
+        with self.roundtrip(in_memory) as on_disk:
+            expected = in_memory.isel(x=[])
+            actual = on_disk.isel(x=[])
+            assert_identical(expected, actual)
+
     def validate_array_type(self, ds):
         # Make sure that only NumpyIndexingAdapter stores a bare np.ndarray.
         def find_and_validate_array(obj):