From 6af547cdd9beac3b18420ccb204f801603e11519 Mon Sep 17 00:00:00 2001
From: Anderson Banihirwe <13301940+andersy005@users.noreply.github.com>
Date: Fri, 22 Mar 2024 19:30:44 -0700
Subject: [PATCH] Handle .oindex and .vindex for the PandasMultiIndexingAdapter
 and PandasIndexingAdapter (#8869)

---
 xarray/core/indexing.py | 103 ++++++++++++++++++++++++++++++++++------
 1 file changed, 89 insertions(+), 14 deletions(-)

diff --git a/xarray/core/indexing.py b/xarray/core/indexing.py
index 82ee4ccb0e4..e26c50c8b90 100644
--- a/xarray/core/indexing.py
+++ b/xarray/core/indexing.py
@@ -1680,11 +1680,65 @@ def _convert_scalar(self, item):
         # a NumPy array.
         return to_0d_array(item)
 
-    def _oindex_get(self, indexer: OuterIndexer):
-        return self.__getitem__(indexer)
+    def _prepare_key(self, key: tuple[Any, ...]) -> tuple[Any, ...]:
+        if isinstance(key, tuple) and len(key) == 1:
+            # unpack key so it can index a pandas.Index object (pandas.Index
+            # objects don't like tuples)
+            (key,) = key
 
-    def _vindex_get(self, indexer: VectorizedIndexer):
-        return self.__getitem__(indexer)
+        return key
+
+    def _handle_result(
+        self, result: Any
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        if isinstance(result, pd.Index):
+            return type(self)(result, dtype=self.dtype)
+        else:
+            return self._convert_scalar(result)
+
+    def _oindex_get(
+        self, indexer: OuterIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        key = self._prepare_key(indexer.tuple)
+
+        if getattr(key, "ndim", 0) > 1:  # Return np-array if multidimensional
+            indexable = NumpyIndexingAdapter(np.asarray(self))
+            return indexable.oindex[indexer]
+
+        result = self.array[key]
+
+        return self._handle_result(result)
+
+    def _vindex_get(
+        self, indexer: VectorizedIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        key = self._prepare_key(indexer.tuple)
+
+        if getattr(key, "ndim", 0) > 1:  # Return np-array if multidimensional
+            indexable = NumpyIndexingAdapter(np.asarray(self))
+            return indexable.vindex[indexer]
+
+        result = self.array[key]
+
+        return self._handle_result(result)
 
     def __getitem__(
         self, indexer: ExplicitIndexer
@@ -1695,22 +1749,15 @@ def __getitem__(
         | np.datetime64
         | np.timedelta64
     ):
-        key = indexer.tuple
-        if isinstance(key, tuple) and len(key) == 1:
-            # unpack key so it can index a pandas.Index object (pandas.Index
-            # objects don't like tuples)
-            (key,) = key
+        key = self._prepare_key(indexer.tuple)
 
         if getattr(key, "ndim", 0) > 1:  # Return np-array if multidimensional
             indexable = NumpyIndexingAdapter(np.asarray(self))
-            return apply_indexer(indexable, indexer)
+            return indexable[indexer]
 
         result = self.array[key]
 
-        if isinstance(result, pd.Index):
-            return type(self)(result, dtype=self.dtype)
-        else:
-            return self._convert_scalar(result)
+        return self._handle_result(result)
 
     def transpose(self, order) -> pd.Index:
         return self.array  # self.array should be always one-dimensional
@@ -1766,6 +1813,34 @@ def _convert_scalar(self, item):
             item = item[idx]
         return super()._convert_scalar(item)
 
+    def _oindex_get(
+        self, indexer: OuterIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        result = super()._oindex_get(indexer)
+        if isinstance(result, type(self)):
+            result.level = self.level
+        return result
+
+    def _vindex_get(
+        self, indexer: VectorizedIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        result = super()._vindex_get(indexer)
+        if isinstance(result, type(self)):
+            result.level = self.level
+        return result
+
     def __getitem__(self, indexer: ExplicitIndexer):
         result = super().__getitem__(indexer)
         if isinstance(result, type(self)):