How to use the elephant.conversion._get_start_stop_from_input function in elephant

Returns
    -------
    time_hist : neo.AnalogSignal
        A neo.AnalogSignal object containing the histogram values.
        `AnalogSignal[j]` is the histogram computed between
        `t_start + j * binsize` and `t_start + (j + 1) * binsize`.

    See also
    --------
    elephant.conversion.BinnedSpikeTrain
    """
    min_tstop = 0
    if t_start is None:
        # Find the internal range for t_start, where all spike trains are
        # defined; cut all spike trains taking that time range only
        max_tstart, min_tstop = conv._get_start_stop_from_input(spiketrains)
        t_start = max_tstart
        if not all([max_tstart == t.t_start for t in spiketrains]):
            warnings.warn(
                "Spiketrains have different t_start values -- "
                "using maximum t_start as t_start.")

    if t_stop is None:
        # Find the internal range for t_stop
        if min_tstop:
            t_stop = min_tstop
            if not all([min_tstop == t.t_stop for t in spiketrains]):
                warnings.warn(
                    "Spiketrains have different t_stop values -- "
                    "using minimum t_stop as t_stop.")
        else:
            min_tstop = conv._get_start_stop_from_input(spiketrains)[1]