Method dot

xarray/core/dataarray.py:5163–5228

Perform dot product of two DataArrays along their shared dims. Equivalent to taking taking tensordot over all shared dims. Parameters ---------- other : DataArray The other array with which the dot product is performed. dim : ..., str, Iterable o

(
        self,
        other: T_Xarray,
        dim: Dims = None,
    )

    @deprecate_dims
    def dot(
        self,
        other: T_Xarray,
        dim: Dims = None,
    ) -> T_Xarray:
        """Perform dot product of two DataArrays along their shared dims.

        Equivalent to taking taking tensordot over all shared dims.

        Parameters
        ----------
        other : DataArray
            The other array with which the dot product is performed.
        dim : ..., str, Iterable of Hashable or None, optional
            Which dimensions to sum over. Ellipsis (`...`) sums over all dimensions.
            If not specified, then all the common dimensions are summed over.

        Returns
        -------
        result : DataArray
            Array resulting from the dot product over all shared dimensions.

        See Also
        --------
        dot
        numpy.tensordot

        Notes
        -----
        This method automatically aligns coordinates by their values (not their order).
        See :ref:`math automatic alignment` and :py:func:`xarray.dot` for more details.

        Examples
        --------
        >>> da_vals = np.arange(6 * 5 * 4).reshape((6, 5, 4))
        >>> da = xr.DataArray(da_vals, dims=["x", "y", "z"])
        >>> dm_vals = np.arange(4)
        >>> dm = xr.DataArray(dm_vals, dims=["z"])

        >>> dm.dims
        ('z',)

        >>> da.dims
        ('x', 'y', 'z')

        >>> dot_result = da.dot(dm)
        >>> dot_result.dims
        ('x', 'y')

        Coordinates are aligned by their values:

        >>> x = xr.DataArray([1, 10], coords=[("foo", ["a", "b"])])
        >>> y = xr.DataArray([2, 20], coords=[("foo", ["b", "a"])])
        >>> x.dot(y)
        <xarray.DataArray ()> Size: 8B
        array(40)

        """