enable xr.ALL_DIMS in xr.dot

doc/whats-new.rst

@@ -34,6 +34,9 @@ New Features
   to reduce over all dimensions. While we have no plans to remove `xr.ALL_DIMS`, we suggest
   using `...`.
   By `Maximilian Roos <https://github.com/max-sixty>`_
+- :py:func:`~xarray.dot`, and :py:func:`~xarray.DataArray.dot` now support the
+  `dims=...` option to sum over the union of dimensions of all input arrays
+  (:issue:`3423`) by `Mathias Hauser <https://github.com/mathause>`_.
 - Added integration tests against `pint <https://pint.readthedocs.io/>`_.
   (:pull:`3238`) by `Justus Magin <https://github.com/keewis>`_.
 

xarray/core/computation.py

@@ -1055,9 +1055,9 @@ def dot(*arrays, dims=None, **kwargs):
     ----------
     arrays: DataArray (or Variable) objects
         Arrays to compute.
-    dims: str or tuple of strings, optional
-        Which dimensions to sum over.
-        If not speciified, then all the common dimensions are summed over.
+    dims: '...', str or tuple of strings, optional
+        Which dimensions to sum over. Ellipsis ('...') sums over all dimensions.
+        If not specified, then all the common dimensions are summed over.
     **kwargs: dict
         Additional keyword arguments passed to numpy.einsum or
         dask.array.einsum
@@ -1070,7 +1070,7 @@ def dot(*arrays, dims=None, **kwargs):
     --------
 
     >>> import numpy as np
-    >>> import xarray as xp
+    >>> import xarray as xr
     >>> da_a = xr.DataArray(np.arange(3 * 2).reshape(3, 2), dims=['a', 'b'])
     >>> da_b = xr.DataArray(np.arange(3 * 2 * 2).reshape(3, 2, 2),
     ...                     dims=['a', 'b', 'c'])
@@ -1117,6 +1117,14 @@ def dot(*arrays, dims=None, **kwargs):
            [273, 446, 619]])
     Dimensions without coordinates: a, d
 
+    >>> xr.dot(da_a, da_b)
+    <xarray.DataArray (c: 2)>
+    array([110, 125])
+    Dimensions without coordinates: c
+
+    >>> xr.dot(da_a, da_b, dims=...)
+    <xarray.DataArray ()>
+    array(235)
     """
     from .dataarray import DataArray
     from .variable import Variable
@@ -1141,7 +1149,9 @@ def dot(*arrays, dims=None, **kwargs):
     einsum_axes = "abcdefghijklmnopqrstuvwxyz"
     dim_map = {d: einsum_axes[i] for i, d in enumerate(all_dims)}
 
-    if dims is None:
+    if dims is ...:
+        dims = all_dims
+    elif dims is None:
         # find dimensions that occur more than one times
         dim_counts = Counter()
         for arr in arrays:

xarray/core/dataarray.py

@@ -2742,9 +2742,9 @@ def dot(
         ----------
         other : DataArray
             The other array with which the dot product is performed.
-        dims: hashable or sequence of hashables, optional
-            Along which dimensions to be summed over. Default all the common
-            dimensions are summed over.
+        dims: '...', hashable or sequence of hashables, optional
+            Which dimensions to sum over. Ellipsis ('...') sums over all dimensions.
+            If not specified, then all the common dimensions are summed over.
 
         Returns
         -------

xarray/tests/test_computation.py

@@ -998,6 +998,23 @@ def test_dot(use_dask):
     assert actual.dims == ("b",)
     assert (actual.data == np.zeros(actual.shape)).all()
 
+    # Ellipsis (...) sums over all dimensions
+    actual = xr.dot(da_a, da_b, dims=...)
+    assert actual.dims == ()
+    assert (actual.data == np.einsum("ij,ijk->", a, b)).all()
+
+    actual = xr.dot(da_a, da_b, da_c, dims=...)
+    assert actual.dims == ()
+    assert (actual.data == np.einsum("ij,ijk,kl-> ", a, b, c)).all()
+
+    actual = xr.dot(da_a, dims=...)
+    assert actual.dims == ()
+    assert (actual.data == np.einsum("ij-> ", a)).all()
+
+    actual = xr.dot(da_a.sel(a=[]), da_a.sel(a=[]), dims=...)
+    assert actual.dims == ()
+    assert (actual.data == np.zeros(actual.shape)).all()
+
     # Invalid cases
     if not use_dask:
         with pytest.raises(TypeError):

xarray/tests/test_dataarray.py

@@ -3925,6 +3925,16 @@ def test_dot(self):
         expected = DataArray(expected_vals, coords=[x, j], dims=["x", "j"])
         assert_equal(expected, actual)
 
+        # Ellipsis: all dims are shared
+        actual = da.dot(da, dims=...)
+        expected = da.dot(da)
+        assert_equal(expected, actual)
+
+        # Ellipsis: not all dims are shared
+        actual = da.dot(dm, dims=...)
+        expected = da.dot(dm, dims=("j", "x", "y", "z"))
+        assert_equal(expected, actual)
+
         with pytest.raises(NotImplementedError):
             da.dot(dm.to_dataset(name="dm"))
         with pytest.raises(TypeError):