def where(cond, x, y):
    """Return elements from `x` or `y` depending on `cond`.

    Performs xarray-like broadcasting across input arguments.

    Parameters
    ----------
    cond : scalar, array, Variable, DataArray or Dataset with boolean dtype
        When True, return values from `x`, otherwise returns values from `y`.
    x, y : scalar, array, Variable, DataArray or Dataset
        Values from which to choose. All dimension coordinates on these objects
        must be aligned with each other and with `cond`.

    Returns
    -------
    In priority order: Dataset, DataArray, Variable or array, whichever
    type appears as an input argument.

    Examples
    --------

    >>> cond = xr.DataArray([True, False], dims=['x'])
    >>> x = xr.DataArray([1, 2], dims=['y'])
    >>> xr.where(cond, x, 0)
    <xarray.DataArray (x: 2, y: 2)>
    array([[1, 2],
           [0, 0]])
    Dimensions without coordinates: x, y

    See also
    --------
    numpy.where : corresponding numpy function
    Dataset.where, DataArray.where : equivalent methods
    """
    # alignment for three arguments is complicated, so don't support it yet
    return apply_ufunc(duck_array_ops.where,
                       cond, x, y,
                       join='exact',
                       dataset_join='exact',
                       dask='allowed')
Return elements from `x` or `y` depending on `cond`.

    Performs xarray-like broadcasting across input arguments.

    Parameters
    ----------
    cond : scalar, array, Variable, DataArray or Dataset with boolean dtype
        When True, return values from `x`, otherwise returns values from `y`.
    x, y : scalar, array, Variable, DataArray or Dataset
        Values from which to choose. All dimension coordinates on these objects
        must be aligned with each other and with `cond`.

    Returns
    -------
    In priority order: Dataset, DataArray, Variable or array, whichever
    type appears as an input argument.

    Examples
    --------

    >>> cond = xr.DataArray([True, False], dims=['x'])
    >>> x = xr.DataArray([1, 2], dims=['y'])
    >>> xr.where(cond, x, 0)
    <xarray.DataArray (x: 2, y: 2)>
    array([[1, 2],
           [0, 0]])
    Dimensions without coordinates: x, y

    See also
    --------
    numpy.where : corresponding numpy function
    Dataset.where, DataArray.where : equivalent methods