BUG: index.getitem raising ValueError with boolean indexer and NA (#45985)

Author: phofl

doc/source/whatsnew/v1.5.0.rst

@@ -326,6 +326,7 @@ Indexing
 - Bug in :meth:`loc.__setitem__` treating ``range`` keys as positional instead of label-based (:issue:`45479`)
 - Bug in :meth:`Series.__setitem__` when setting ``boolean`` dtype values containing ``NA`` incorrectly raising instead of casting to ``boolean`` dtype (:issue:`45462`)
 - Bug in :meth:`Series.__setitem__` where setting :attr:`NA` into a numeric-dtpye :class:`Series` would incorrectly upcast to object-dtype rather than treating the value as ``np.nan`` (:issue:`44199`)
+- Bug in :meth:`Index.__getitem__`  raising ``ValueError`` when indexer is from boolean dtype with ``NA`` (:issue:`45806`)
 - Bug in :meth:`Series.mask` with ``inplace=True`` or setting values with a boolean mask with small integer dtypes incorrectly raising (:issue:`45750`)
 - Bug in :meth:`DataFrame.mask` with ``inplace=True`` and ``ExtensionDtype`` columns incorrectly raising (:issue:`45577`)
 - Bug in getting a column from a DataFrame with an object-dtype row index with datetime-like values: the resulting Series now preserves the exact object-dtype Index from the parent DataFrame (:issue:`42950`)

pandas/core/indexes/base.py

@@ -5226,7 +5226,10 @@ def __getitem__(self, key):
             #  takes 166 µs + 2.1 ms and cuts the ndarray.__getitem__
             #  time below from 3.8 ms to 496 µs
             # if we already have ndarray[bool], the overhead is 1.4 µs or .25%
-            key = np.asarray(key, dtype=bool)
+            if is_extension_array_dtype(getattr(key, "dtype", None)):
+                key = key.to_numpy(dtype=bool, na_value=False)
+            else:
+                key = np.asarray(key, dtype=bool)
 
         result = getitem(key)
         # Because we ruled out integer above, we always get an arraylike here

pandas/tests/indexes/base_class/test_indexing.py

@@ -76,3 +76,11 @@ def test_get_loc_nan_object_dtype_nonmonotonic_nonunique(self):
         # we don't match at all on mismatched NA
         with pytest.raises(KeyError, match="NaT"):
             idx.get_loc(NaT)
+
+
+def test_getitem_boolean_ea_indexer():
+    # GH#45806
+    ser = pd.Series([True, False, pd.NA], dtype="boolean")
+    result = ser.index[ser]
+    expected = Index([0])
+    tm.assert_index_equal(result, expected)