Add expand_dims (#8407)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Anderson Banihirwe <13301940+andersy005@users.noreply.github.com>

Author: 3 people

xarray/core/variable.py

@@ -2596,7 +2596,7 @@ 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
+        from xarray.namedarray._typing import _default as _default_named
 
         if sparse_format is _default:
             sparse_format = _default_named

xarray/namedarray/_array_api.py

@@ -7,7 +7,11 @@
 import numpy as np
 
 from xarray.namedarray._typing import (
+    Default,
     _arrayapi,
+    _Axis,
+    _default,
+    _Dim,
     _DType,
     _ScalarType,
     _ShapeType,
@@ -144,3 +148,51 @@ def real(
     xp = _get_data_namespace(x)
     out = x._new(data=xp.real(x._data))
     return out
+
+
+# %% Manipulation functions
+def expand_dims(
+    x: NamedArray[Any, _DType],
+    /,
+    *,
+    dim: _Dim | Default = _default,
+    axis: _Axis = 0,
+) -> NamedArray[Any, _DType]:
+    """
+    Expands the shape of an array by inserting a new dimension of size one at the
+    position specified by dims.
+
+    Parameters
+    ----------
+    x :
+        Array to expand.
+    dim :
+        Dimension name. New dimension will be stored in the axis position.
+    axis :
+        (Not recommended) Axis position (zero-based). Default is 0.
+
+    Returns
+    -------
+        out :
+            An expanded output array having the same data type as x.
+
+    Examples
+    --------
+    >>> x = NamedArray(("x", "y"), nxp.asarray([[1.0, 2.0], [3.0, 4.0]]))
+    >>> expand_dims(x)
+    <xarray.NamedArray (dim_2: 1, x: 2, y: 2)>
+    Array([[[1., 2.],
+            [3., 4.]]], dtype=float64)
+    >>> expand_dims(x, dim="z")
+    <xarray.NamedArray (z: 1, x: 2, y: 2)>
+    Array([[[1., 2.],
+            [3., 4.]]], dtype=float64)
+    """
+    xp = _get_data_namespace(x)
+    dims = x.dims
+    if dim is _default:
+        dim = f"dim_{len(dims)}"
+    d = list(dims)
+    d.insert(axis, dim)
+    out = x._new(dims=tuple(d), data=xp.expand_dims(x._data, axis=axis))
+    return out

xarray/namedarray/_typing.py

@@ -1,10 +1,12 @@
 from __future__ import annotations
 
 from collections.abc import Hashable, Iterable, Mapping, Sequence
+from enum import Enum
 from types import ModuleType
 from typing import (
     Any,
     Callable,
+    Final,
     Protocol,
     SupportsIndex,
     TypeVar,
@@ -15,6 +17,14 @@
 
 import numpy as np
 
+
+# Singleton type, as per https://github.com/python/typing/pull/240
+class Default(Enum):
+    token: Final = 0
+
+
+_default = Default.token
+
 # https://stackoverflow.com/questions/74633074/how-to-type-hint-a-generic-numpy-array
 _T = TypeVar("_T")
 _T_co = TypeVar("_T_co", covariant=True)
@@ -49,6 +59,10 @@ def dtype(self) -> _DType_co:
 _ShapeType = TypeVar("_ShapeType", bound=Any)
 _ShapeType_co = TypeVar("_ShapeType_co", bound=Any, covariant=True)
 
+_Axis = int
+_Axes = tuple[_Axis, ...]
+_AxisLike = Union[_Axis, _Axes]
+
 _Chunks = tuple[_Shape, ...]
 
 _Dim = Hashable

xarray/namedarray/core.py

@@ -25,6 +25,7 @@
     _arrayapi,
     _arrayfunction_or_api,
     _chunkedarray,
+    _default,
     _dtype,
     _DType_co,
     _ScalarType_co,
@@ -33,13 +34,14 @@
     _SupportsImag,
     _SupportsReal,
 )
-from xarray.namedarray.utils import _default, is_duck_dask_array, to_0d_object_array
+from xarray.namedarray.utils import is_duck_dask_array, to_0d_object_array
 
 if TYPE_CHECKING:
     from numpy.typing import ArrayLike, NDArray
 
     from xarray.core.types import Dims
     from xarray.namedarray._typing import (
+        Default,
         _AttrsLike,
         _Chunks,
         _Dim,
@@ -52,7 +54,6 @@
         _ShapeType,
         duckarray,
     )
-    from xarray.namedarray.utils import Default
 
     try:
         from dask.typing import (

xarray/namedarray/utils.py

@@ -2,12 +2,7 @@
 
 import sys
 from collections.abc import Hashable
-from enum import Enum
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Final,
-)
+from typing import TYPE_CHECKING, Any
 
 import numpy as np
 
@@ -31,14 +26,6 @@
         DaskCollection: Any = NDArray  # type: ignore
 
 
-# Singleton type, as per https://github.com/python/typing/pull/240
-class Default(Enum):
-    token: Final = 0
-
-
-_default = Default.token
-
-
 def module_available(module: str) -> bool:
     """Checks whether a module is installed without importing it.
 

xarray/tests/test_namedarray.py

@@ -10,23 +10,27 @@
 import pytest
 
 from xarray.core.indexing import ExplicitlyIndexed
-from xarray.namedarray._typing import _arrayfunction_or_api, _DType_co, _ShapeType_co
+from xarray.namedarray._typing import (
+    _arrayfunction_or_api,
+    _default,
+    _DType_co,
+    _ShapeType_co,
+)
 from xarray.namedarray.core import NamedArray, from_array
-from xarray.namedarray.utils import _default
 
 if TYPE_CHECKING:
     from types import ModuleType
 
     from numpy.typing import ArrayLike, DTypeLike, NDArray
 
     from xarray.namedarray._typing import (
+        Default,
         _AttrsLike,
         _DimsLike,
         _DType,
         _Shape,
         duckarray,
     )
-    from xarray.namedarray.utils import Default
 
 
 class CustomArrayBase(Generic[_ShapeType_co, _DType_co]):