How to use the solarforecastarbiter.reference_forecasts.utils.get_data_start_end function in solarforecastarbiter

Notes
    -----
    For non-intraday net load forecasts, this function will use a weekahead
    persistence due to the fact that net load exhibits stronger correlation
    week-to-week than day-to-day. For example, the net load on a Monday tends
    to look more similar to the previous Monday that it does to the previous
    day (Sunday).
    """
    utils.check_persistence_compatibility(observation, forecast, index)
    forecast_start, forecast_end = utils.get_forecast_start_end(
        forecast, issue_time, False)
    intraday = utils._is_intraday(forecast)

    if load_data is None:
        load_data = _default_load_data(session)
    data_start, data_end = utils.get_data_start_end(
        observation, forecast, run_time, issue_time)
    if data_end > run_time:
        raise ValueError(
            'Persistence forecast requires data from after run_time')

    if isinstance(forecast, datamodel.ProbabilisticForecast):
        cvs = [f.constant_value for f in forecast.constant_values]
        fx = persistence.persistence_probabilistic(
            observation, data_start, data_end, forecast_start, forecast_end,
            forecast.interval_length, forecast.interval_label, load_data,
            forecast.axis, cvs)
    elif intraday and index:
        fx = persistence.persistence_scalar_index(
            observation, data_start, data_end, forecast_start, forecast_end,
            forecast.interval_length, forecast.interval_label, load_data)
    elif intraday and not index:

def _issue_time_generator(observation, fx, obs_mint, obs_maxt, next_issue_time,
                          max_run_time):
    # now find all the run times that can be made based on the
    # last observation timestamp
    while next_issue_time <= max_run_time:
        data_start, data_end = utils.get_data_start_end(
            observation, fx, next_issue_time, next_issue_time)
        if data_end > obs_maxt:
            break

        if data_start > obs_mint:
            yield next_issue_time
        next_issue_time = utils.get_next_issue_time(
            fx, next_issue_time + pd.Timedelta('1ns'))

else:
            fx_mint, fx_maxt = session.get_forecast_time_range(fx.forecast_id)
        # find the next issue time for the forecast based on the last value
        # in the forecast series
        if pd.isna(fx_maxt):
            # if there is no forecast yet, go back a bit from the last
            # observation. Don't use the start of observations, since it
            # could really stress the workers if we have a few years of
            # data before deciding to make a persistence fx
            next_issue_time = utils.get_next_issue_time(
                fx, obs_maxt - fx.run_length)
        else:
            next_issue_time = utils.find_next_issue_time_from_last_forecast(
                fx, fx_maxt)

        data_start, _ = utils.get_data_start_end(
            observation, fx, next_issue_time, next_issue_time)
        issue_times = tuple(_issue_time_generator(
            observation, fx, obs_mint, obs_maxt,
            next_issue_time, max_run_time))

        if len(issue_times) == 0:
            continue

        out = namedtuple(
            'PersistenceParameters',
            ['forecast', 'observation', 'index', 'data_start',
             'issue_times'])

        yield out(fx, observation, index, data_start, issue_times)