How to use the xrft.power_spectrum function in xrft

* Branstator, Grant, and Haiyan Teng. “Two Limits of Initial-Value
        Decadal Predictability in a CGCM." Journal of Climate 23, no. 23
        (August 27, 2010): 6292-6311. https://doi.org/10/bwq92h.

    See also:
    https://xrft.readthedocs.io/en/latest/api.html#xrft.xrft.power_spectrum
    """
    # set nans to 0
    if isinstance(da, xr.Dataset):
        raise ValueError('require xr.Dataset')
    da = da.fillna(0.0)
    # dim should be list
    if isinstance(dim, str):
        dim = [dim]
    assert isinstance(dim, list)
    ps = power_spectrum(da, dim=dim, **kwargs)
    # take pos
    for d in dim:
        ps = ps.where(ps[f'freq_{d}'] > 0)
    # weighted average
    vwmp = ps
    for d in dim:
        vwmp = vwmp.sum(f'freq_{d}') / ((vwmp * vwmp[f'freq_{d}']).sum(f'freq_{d}'))
    for d in dim:
        del vwmp[f'freq_{d}_spacing']
    # try to copy coords
    try:
        vwmp = copy_coords_from_to(da.drop(dim), vwmp)
    except ValueError:
        warnings.warn("Couldn't keep coords.")
    return vwmp