def segment_snrs(filters, stilde, psd, low_frequency_cutoff):
    """ This functions calculates the snr of each bank veto template against
    the segment

    Parameters
    ----------
    filters: list of FrequencySeries
        The list of bank veto templates filters.
    stilde: FrequencySeries
        The current segment of data.
    psd: FrequencySeries
    low_frequency_cutoff: float

    Returns
    -------
    snr (list): List of snr time series.
    norm (list): List of normalizations factors for the snr time series.
    """
    snrs = []
    norms = []

    for bank_template in filters:
        # For every template compute the snr against the stilde segment
        snr, _, norm = matched_filter_core(
                bank_template, stilde, h_norm=bank_template.sigmasq(psd),
                psd=None, low_frequency_cutoff=low_frequency_cutoff)
        # SNR time series stored here
        snrs.append(snr)
        # Template normalization factor stored here
        norms.append(norm)

    return snrs, norms
This functions calculates the snr of each bank veto template against
    the segment

    Parameters
    ----------
    filters: list of FrequencySeries
        The list of bank veto templates filters.
    stilde: FrequencySeries
        The current segment of data.
    psd: FrequencySeries
    low_frequency_cutoff: float

    Returns
    -------
    snr (list): List of snr time series.
    norm (list): List of normalizations factors for the snr time series.