Implement setitem syntax for .oindex and .vindex properties (#8845)

* Implement setitem syntax for `.oindex` and `.vindex` properties

* Apply suggestions from code review

Co-authored-by: Deepak Cherian <dcherian@users.noreply.github.com>

* use getter and setter properties instead of func_get and func_set methods

* delete unnecessary _indexing_array_and_key method

* Add tests for IndexCallable class

* fix bug/unnecessary code introduced in #8790

* add unit tests

---------

Co-authored-by: Deepak Cherian <dcherian@users.noreply.github.com>

xarray/core/indexing.py

@@ -326,18 +326,23 @@ def as_integer_slice(value):
 
 
 class IndexCallable:
-    """Provide getitem syntax for a callable object."""
+    """Provide getitem and setitem syntax for callable objects."""
 
-    __slots__ = ("func",)
+    __slots__ = ("getter", "setter")
 
-    def __init__(self, func):
-        self.func = func
+    def __init__(self, getter, setter=None):
+        self.getter = getter
+        self.setter = setter
 
     def __getitem__(self, key):
-        return self.func(key)
+        return self.getter(key)
 
     def __setitem__(self, key, value):
-        raise NotImplementedError
+        if self.setter is None:
+            raise NotImplementedError(
+                "Setting values is not supported for this indexer."
+            )
+        self.setter(key, value)
 
 
 class BasicIndexer(ExplicitIndexer):
@@ -486,10 +491,24 @@ def __array__(self, dtype: np.typing.DTypeLike = None) -> np.ndarray:
         return np.asarray(self.get_duck_array(), dtype=dtype)
 
     def _oindex_get(self, key):
-        raise NotImplementedError("This method should be overridden")
+        raise NotImplementedError(
+            f"{self.__class__.__name__}._oindex_get method should be overridden"
+        )
 
     def _vindex_get(self, key):
-        raise NotImplementedError("This method should be overridden")
+        raise NotImplementedError(
+            f"{self.__class__.__name__}._vindex_get method should be overridden"
+        )
+
+    def _oindex_set(self, key, value):
+        raise NotImplementedError(
+            f"{self.__class__.__name__}._oindex_set method should be overridden"
+        )
+
+    def _vindex_set(self, key, value):
+        raise NotImplementedError(
+            f"{self.__class__.__name__}._vindex_set method should be overridden"
+        )
 
     def _check_and_raise_if_non_basic_indexer(self, key):
         if isinstance(key, (VectorizedIndexer, OuterIndexer)):
@@ -500,11 +519,11 @@ def _check_and_raise_if_non_basic_indexer(self, key):
 
     @property
     def oindex(self):
-        return IndexCallable(self._oindex_get)
+        return IndexCallable(self._oindex_get, self._oindex_set)
 
     @property
     def vindex(self):
-        return IndexCallable(self._vindex_get)
+        return IndexCallable(self._vindex_get, self._vindex_set)
 
 
 class ImplicitToExplicitIndexingAdapter(NDArrayMixin):
@@ -616,12 +635,18 @@ def __getitem__(self, indexer):
         self._check_and_raise_if_non_basic_indexer(indexer)
         return type(self)(self.array, self._updated_key(indexer))
 
+    def _vindex_set(self, key, value):
+        raise NotImplementedError(
+            "Lazy item assignment with the vectorized indexer is not yet "
+            "implemented. Load your data first by .load() or compute()."
+        )
+
+    def _oindex_set(self, key, value):
+        full_key = self._updated_key(key)
+        self.array.oindex[full_key] = value
+
     def __setitem__(self, key, value):
-        if isinstance(key, VectorizedIndexer):
-            raise NotImplementedError(
-                "Lazy item assignment with the vectorized indexer is not yet "
-                "implemented. Load your data first by .load() or compute()."
-            )
+        self._check_and_raise_if_non_basic_indexer(key)
         full_key = self._updated_key(key)
         self.array[full_key] = value
 
@@ -657,7 +682,6 @@ def shape(self) -> tuple[int, ...]:
         return np.broadcast(*self.key.tuple).shape
 
     def get_duck_array(self):
-
         if isinstance(self.array, ExplicitlyIndexedNDArrayMixin):
             array = apply_indexer(self.array, self.key)
         else:
@@ -739,8 +763,18 @@ def __getitem__(self, key):
     def transpose(self, order):
         return self.array.transpose(order)
 
+    def _vindex_set(self, key, value):
+        self._ensure_copied()
+        self.array.vindex[key] = value
+
+    def _oindex_set(self, key, value):
+        self._ensure_copied()
+        self.array.oindex[key] = value
+
     def __setitem__(self, key, value):
+        self._check_and_raise_if_non_basic_indexer(key)
         self._ensure_copied()
+
         self.array[key] = value
 
     def __deepcopy__(self, memo):
@@ -779,7 +813,14 @@ def __getitem__(self, key):
     def transpose(self, order):
         return self.array.transpose(order)
 
+    def _vindex_set(self, key, value):
+        self.array.vindex[key] = value
+
+    def _oindex_set(self, key, value):
+        self.array.oindex[key] = value
+
     def __setitem__(self, key, value):
+        self._check_and_raise_if_non_basic_indexer(key)
         self.array[key] = value
 
 
@@ -950,6 +991,16 @@ def apply_indexer(indexable, indexer):
         return indexable[indexer]
 
 
+def set_with_indexer(indexable, indexer, value):
+    """Set values in an indexable object using an indexer."""
+    if isinstance(indexer, VectorizedIndexer):
+        indexable.vindex[indexer] = value
+    elif isinstance(indexer, OuterIndexer):
+        indexable.oindex[indexer] = value
+    else:
+        indexable[indexer] = value
+
+
 def decompose_indexer(
     indexer: ExplicitIndexer, shape: tuple[int, ...], indexing_support: IndexingSupport
 ) -> tuple[ExplicitIndexer, ExplicitIndexer]:
@@ -1399,24 +1450,6 @@ def __init__(self, array):
             )
         self.array = array
 
-    def _indexing_array_and_key(self, key):
-        if isinstance(key, OuterIndexer):
-            array = self.array
-            key = _outer_to_numpy_indexer(key, self.array.shape)
-        elif isinstance(key, VectorizedIndexer):
-            array = NumpyVIndexAdapter(self.array)
-            key = key.tuple
-        elif isinstance(key, BasicIndexer):
-            array = self.array
-            # We want 0d slices rather than scalars. This is achieved by
-            # appending an ellipsis (see
-            # https://numpy.org/doc/stable/reference/arrays.indexing.html#detailed-notes).
-            key = key.tuple + (Ellipsis,)
-        else:
-            raise TypeError(f"unexpected key type: {type(key)}")
-
-        return array, key
-
     def transpose(self, order):
         return self.array.transpose(order)
 
@@ -1430,22 +1463,43 @@ def _vindex_get(self, key):
 
     def __getitem__(self, key):
         self._check_and_raise_if_non_basic_indexer(key)
-        array, key = self._indexing_array_and_key(key)
+
+        array = self.array
+        # We want 0d slices rather than scalars. This is achieved by
+        # appending an ellipsis (see
+        # https://numpy.org/doc/stable/reference/arrays.indexing.html#detailed-notes).
+        key = key.tuple + (Ellipsis,)
         return array[key]
 
-    def __setitem__(self, key, value):
-        array, key = self._indexing_array_and_key(key)
+    def _safe_setitem(self, array, key, value):
         try:
             array[key] = value
-        except ValueError:
+        except ValueError as exc:
             # More informative exception if read-only view
             if not array.flags.writeable and not array.flags.owndata:
                 raise ValueError(
                     "Assignment destination is a view.  "
                     "Do you want to .copy() array first?"
                 )
             else:
-                raise
+                raise exc
+
+    def _oindex_set(self, key, value):
+        key = _outer_to_numpy_indexer(key, self.array.shape)
+        self._safe_setitem(self.array, key, value)
+
+    def _vindex_set(self, key, value):
+        array = NumpyVIndexAdapter(self.array)
+        self._safe_setitem(array, key.tuple, value)
+
+    def __setitem__(self, key, value):
+        self._check_and_raise_if_non_basic_indexer(key)
+        array = self.array
+        # We want 0d slices rather than scalars. This is achieved by
+        # appending an ellipsis (see
+        # https://numpy.org/doc/stable/reference/arrays.indexing.html#detailed-notes).
+        key = key.tuple + (Ellipsis,)
+        self._safe_setitem(array, key, value)
 
 
 class NdArrayLikeIndexingAdapter(NumpyIndexingAdapter):
@@ -1488,13 +1542,15 @@ def __getitem__(self, key):
         self._check_and_raise_if_non_basic_indexer(key)
         return self.array[key.tuple]
 
+    def _oindex_set(self, key, value):
+        self.array[key.tuple] = value
+
+    def _vindex_set(self, key, value):
+        raise TypeError("Vectorized indexing is not supported")
+
     def __setitem__(self, key, value):
-        if isinstance(key, (BasicIndexer, OuterIndexer)):
-            self.array[key.tuple] = value
-        elif isinstance(key, VectorizedIndexer):
-            raise TypeError("Vectorized indexing is not supported")
-        else:
-            raise TypeError(f"Unrecognized indexer: {key}")
+        self._check_and_raise_if_non_basic_indexer(key)
+        self.array[key.tuple] = value
 
     def transpose(self, order):
         xp = self.array.__array_namespace__()
@@ -1530,19 +1586,20 @@ def __getitem__(self, key):
         self._check_and_raise_if_non_basic_indexer(key)
         return self.array[key.tuple]
 
+    def _oindex_set(self, key, value):
+        num_non_slices = sum(0 if isinstance(k, slice) else 1 for k in key.tuple)
+        if num_non_slices > 1:
+            raise NotImplementedError(
+                "xarray can't set arrays with multiple " "array indices to dask yet."
+            )
+        self.array[key.tuple] = value
+
+    def _vindex_set(self, key, value):
+        self.array.vindex[key.tuple] = value
+
     def __setitem__(self, key, value):
-        if isinstance(key, BasicIndexer):
-            self.array[key.tuple] = value
-        elif isinstance(key, VectorizedIndexer):
-            self.array.vindex[key.tuple] = value
-        elif isinstance(key, OuterIndexer):
-            num_non_slices = sum(0 if isinstance(k, slice) else 1 for k in key.tuple)
-            if num_non_slices > 1:
-                raise NotImplementedError(
-                    "xarray can't set arrays with multiple "
-                    "array indices to dask yet."
-                )
-            self.array[key.tuple] = value
+        self._check_and_raise_if_non_basic_indexer(key)
+        self.array[key.tuple] = value
 
     def transpose(self, order):
         return self.array.transpose(order)

xarray/core/variable.py

@@ -849,7 +849,7 @@ def __setitem__(self, key, value):
             value = np.moveaxis(value, new_order, range(len(new_order)))
 
         indexable = as_indexable(self._data)
-        indexable[index_tuple] = value
+        indexing.set_with_indexer(indexable, index_tuple, value)
 
     @property
     def encoding(self) -> dict[Any, Any]:

xarray/tests/test_indexing.py

@@ -23,6 +23,28 @@
 B = IndexerMaker(indexing.BasicIndexer)
 
 
+class TestIndexCallable:
+    def test_getitem(self):
+        def getter(key):
+            return key * 2
+
+        indexer = indexing.IndexCallable(getter)
+        assert indexer[3] == 6
+        assert indexer[0] == 0
+        assert indexer[-1] == -2
+
+    def test_setitem(self):
+        def getter(key):
+            return key * 2
+
+        def setter(key, value):
+            raise NotImplementedError("Setter not implemented")
+
+        indexer = indexing.IndexCallable(getter, setter)
+        with pytest.raises(NotImplementedError):
+            indexer[3] = 6
+
+
 class TestIndexers:
     def set_to_zero(self, x, i):
         x = x.copy()
@@ -361,15 +383,8 @@ def test_vectorized_lazily_indexed_array(self) -> None:
 
         def check_indexing(v_eager, v_lazy, indexers):
             for indexer in indexers:
-                if isinstance(indexer, indexing.VectorizedIndexer):
-                    actual = v_lazy.vindex[indexer]
-                    expected = v_eager.vindex[indexer]
-                elif isinstance(indexer, indexing.OuterIndexer):
-                    actual = v_lazy.oindex[indexer]
-                    expected = v_eager.oindex[indexer]
-                else:
-                    actual = v_lazy[indexer]
-                    expected = v_eager[indexer]
+                actual = v_lazy[indexer]
+                expected = v_eager[indexer]
                 assert expected.shape == actual.shape
                 assert isinstance(
                     actual._data,
@@ -406,6 +421,41 @@ def check_indexing(v_eager, v_lazy, indexers):
         ]
         check_indexing(v_eager, v_lazy, indexers)
 
+    def test_lazily_indexed_array_vindex_setitem(self) -> None:
+
+        lazy = indexing.LazilyIndexedArray(np.random.rand(10, 20, 30))
+
+        # vectorized indexing
+        indexer = indexing.VectorizedIndexer(
+            (np.array([0, 1]), np.array([0, 1]), slice(None, None, None))
+        )
+        with pytest.raises(
+            NotImplementedError,
+            match=r"Lazy item assignment with the vectorized indexer is not yet",
+        ):
+            lazy.vindex[indexer] = 0
+
+    @pytest.mark.parametrize(
+        "indexer_class, key, value",
+        [
+            (indexing.OuterIndexer, (0, 1, slice(None, None, None)), 10),
+            (indexing.BasicIndexer, (0, 1, slice(None, None, None)), 10),
+        ],
+    )
+    def test_lazily_indexed_array_setitem(self, indexer_class, key, value) -> None:
+        original = np.random.rand(10, 20, 30)
+        x = indexing.NumpyIndexingAdapter(original)
+        lazy = indexing.LazilyIndexedArray(x)
+
+        if indexer_class is indexing.BasicIndexer:
+            indexer = indexer_class(key)
+            lazy[indexer] = value
+        elif indexer_class is indexing.OuterIndexer:
+            indexer = indexer_class(key)
+            lazy.oindex[indexer] = value
+
+        assert_array_equal(original[key], value)
+
 
 class TestCopyOnWriteArray:
     def test_setitem(self) -> None: