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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ensure_time_as_index(ds):
 """Ensures that time is an indexed coordinate on relevant quantites. Sometimes when the data we load from disk has only one timestep, the indexing of time-defined quantities in the resulting xarray.Dataset gets messed up, in that the time bounds array and data variables don't get indexed by time, even though they should. Therefore, we need this helper function to (possibly) correct this. Note that this must be applied before CF-conventions are decoded; otherwise it casts ``np.datetime64[ns]`` as ``int`` values. Parameters ds : Dataset Dataset with a time coordinate Returns ------- Dataset """

    time_indexed_coords = {TIME_WEIGHTS_STR, TIME_BOUNDS_STR}
    time_indexed_vars = set(ds.data_vars).union(time_indexed_coords)
    time_indexed_vars = time_indexed_vars.intersection(ds.variables)
    variables_to_replace = {}
    for name in time_indexed_vars:
        if TIME_STR not in ds[name].indexes:
            da = ds[name]
            if TIME_STR not in da.dims:
                da = ds[name].expand_dims(TIME_STR)
            da = da.assign_coords(**{TIME_STR: ds[TIME_STR]})
            variables_to_replace[name] = da
    return ds.assign(**variables_to_replace)