Fix sparse typing (#8387)

* Fix sparse typing

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update variable.py

* typos

* Update variable.py

* Update variable.py

* Update variable.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update variable.py

* Update variable.py

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

xarray/core/variable.py

@@ -2595,6 +2595,28 @@ def argmax(
         """
         return self._unravel_argminmax("argmax", dim, axis, keep_attrs, skipna)
 
+    def _as_sparse(self, sparse_format=_default, fill_value=_default) -> Variable:
+        """
+        Use sparse-array as backend.
+        """
+        from xarray.namedarray.utils import _default as _default_named
+
+        if sparse_format is _default:
+            sparse_format = _default_named
+
+        if fill_value is _default:
+            fill_value = _default_named
+
+        out = super()._as_sparse(sparse_format, fill_value)
+        return cast("Variable", out)
+
+    def _to_dense(self) -> Variable:
+        """
+        Change backend from sparse to np.array.
+        """
+        out = super()._to_dense()
+        return cast("Variable", out)
+
 
 class IndexVariable(Variable):
     """Wrapper for accommodating a pandas.Index in an xarray.Variable.

xarray/namedarray/_typing.py

@@ -248,7 +248,7 @@ class _sparsearrayfunction(
     Corresponds to np.ndarray.
     """
 
-    def todense(self) -> NDArray[_ScalarType_co]:
+    def todense(self) -> np.ndarray[Any, _DType_co]:
         ...
 
 
@@ -262,9 +262,14 @@ class _sparsearrayapi(
     Corresponds to np.ndarray.
     """
 
-    def todense(self) -> NDArray[_ScalarType_co]:
+    def todense(self) -> np.ndarray[Any, _DType_co]:
         ...
 
 
 # NamedArray can most likely use both __array_function__ and __array_namespace__:
 _sparsearrayfunction_or_api = (_sparsearrayfunction, _sparsearrayapi)
+
+sparseduckarray = Union[
+    _sparsearrayfunction[_ShapeType_co, _DType_co],
+    _sparsearrayapi[_ShapeType_co, _DType_co],
+]

xarray/namedarray/core.py

@@ -29,6 +29,7 @@
     _DType_co,
     _ScalarType_co,
     _ShapeType_co,
+    _sparsearrayfunction_or_api,
     _SupportsImag,
     _SupportsReal,
 )
@@ -810,9 +811,9 @@ def _as_sparse(
         self,
         sparse_format: Literal["coo"] | Default = _default,
         fill_value: ArrayLike | Default = _default,
-    ) -> Self:
+    ) -> NamedArray[Any, _DType_co]:
         """
-        use sparse-array as backend.
+        Use sparse-array as backend.
         """
         import sparse
 
@@ -832,18 +833,15 @@ def _as_sparse(
             raise ValueError(f"{sparse_format} is not a valid sparse format") from exc
 
         data = as_sparse(astype(self, dtype).data, fill_value=fill_value)
-        return self._replace(data=data)
+        return self._new(data=data)
 
-    def _to_dense(self) -> Self:
+    def _to_dense(self) -> NamedArray[Any, _DType_co]:
         """
-        Change backend from sparse to np.array
+        Change backend from sparse to np.array.
         """
-        from xarray.namedarray._typing import _sparsearrayfunction_or_api
-
         if isinstance(self._data, _sparsearrayfunction_or_api):
-            # return self._replace(data=self._data.todense())
-            data_: np.ndarray[Any, Any] = self._data.todense()
-            return self._replace(data=data_)
+            data_dense: np.ndarray[Any, _DType_co] = self._data.todense()
+            return self._new(data=data_dense)
         else:
             raise TypeError("self.data is not a sparse array")