How to use the solarforecastarbiter.pvmodel function in solarforecastarbiter

def _ghi_to_dni_dhi(latitude, longitude, elevation, ghi):
    """
    Calculate DNI, DHI from GHI and calculated solar position.
    """
    solar_position = pvmodel.calculate_solar_position(
        latitude, longitude, elevation, ghi.index)
    dni, dhi = pvmodel.complete_irradiance_components(
        ghi, solar_position['zenith'])

    def solar_pos_calculator(): return solar_position
    return dni, dhi, solar_pos_calculator

Returns
    -------
    timestamp_flag, night_flag, poa_clearsky_flag : pandas.Series
        Integer bitmask series from
        :py:func:`.validator.check_timestamp_spacing`,
        :py:func:`.validator.check_irradiance_day_night`,
        :py:func:`.validator.check_poa_clearsky` respectively
    """
    solar_position, dni_extra, timestamp_flag, night_flag = _solpos_dni_extra(
        observation, values)
    clearsky = pvmodel.calculate_clearsky(
        observation.site.latitude, observation.site.longitude,
        observation.site.elevation, solar_position['apparent_zenith'])
    aoi_func = pvmodel.aoi_func_factory(observation.site.modeling_parameters)
    poa_clearsky = pvmodel.calculate_poa_effective(
        aoi_func=aoi_func, apparent_zenith=solar_position['apparent_zenith'],
        azimuth=solar_position['azimuth'], ghi=clearsky['ghi'],
        dni=clearsky['dni'], dhi=clearsky['dhi'])
    poa_clearsky_flag = validator.check_poa_clearsky(values, poa_clearsky,
                                                     _return_mask=True)
    return timestamp_flag, night_flag, poa_clearsky_flag

same as the observation interval label.
    """
    # ensure that we're using times rounded to multiple of interval_length
    _check_intervals_times(observation.interval_label, data_start, data_end,
                           forecast_start, forecast_end,
                           observation.interval_length)

    # get observation data for specified range
    obs = load_data(observation, data_start, data_end)

    # partial-up the metadata for solar position and
    # clearsky calculation clarity and consistency
    site = observation.site
    calc_solpos = partial(pvmodel.calculate_solar_position,
                          site.latitude, site.longitude, site.elevation)
    calc_cs = partial(pvmodel.calculate_clearsky,
                      site.latitude, site.longitude, site.elevation)

    # Calculate solar position and clearsky for obs time range.
    # if data is instantaneous, calculate at the obs time.
    # else (if data is interval average), calculate at 1 minute resolution to
    # reduce errors from changing solar position during persistence data range.
    # Later, modeled clear sky or ac power will be averaged over the data range
    closed = datamodel.CLOSED_MAPPING[observation.interval_label]
    if closed is None:
        freq = observation.interval_length
    else:
        freq = pd.Timedelta('1min')
    obs_range = pd.date_range(start=data_start, end=data_end, freq=freq,
                              closed=closed)
    solar_position_obs = calc_solpos(obs_range)
    clearsky_obs = calc_cs(solar_position_obs['apparent_zenith'])

2. Estimate cloudy sky DNI and DHI using the Erbs model.

    Parameters
    ----------
    site : datamodel.Site
    cloud_cover : Series
        Cloud cover in %.
    zenith : Series
        Solar zenith

    Returns
    -------
    ghi : pd.Series, dni : pd.Series, dhi : pd.Series
    """
    ghi = cloud_cover_to_ghi_linear(cloud_cover, ghi_clear)
    dni, dhi = pvmodel.complete_irradiance_components(ghi, zenith)
    return ghi, dni, dhi