def mtie(data, rate=1.0, data_type="phase", taus=None):
    """ Maximum Time Interval Error.

    Parameters
    ----------
    data: np.array
        Input data. Provide either phase or frequency (fractional,
        adimensional).
    rate: float
        The sampling rate for data, in Hz. Defaults to 1.0
    data_type: {'phase', 'freq'}
        Data type, i.e. phase or frequency. Defaults to "phase".
    taus: np.array
        Array of tau values, in seconds, for which to compute statistic.
        Optionally set taus=["all"|"octave"|"decade"] for automatic
        tau-list generation.

    Notes
    -----
    this seems to correspond to Stable32 setting "Fast(u)"
    Stable32 also has "Decade" and "Octave" modes where the
    dataset is extended somehow?
    """
    phase = input_to_phase(data, rate, data_type)
    (phase, m, taus_used) = tau_generator(phase, rate, taus)
    devs = np.zeros_like(taus_used)
    deverrs = np.zeros_like(taus_used)
    ns = np.zeros_like(taus_used)

    for idx, mj in enumerate(m):
        rw = mtie_rolling_window(phase, int(mj + 1))
        win_max = np.max(rw, axis=1)
        win_min = np.min(rw, axis=1)
        tie = win_max - win_min
        dev = np.max(tie)
        ncount = phase.shape[0] - mj
        devs[idx] = dev
        deverrs[idx] = dev / np.sqrt(ncount)
        ns[idx] = ncount

    return remove_small_ns(taus_used, devs, deverrs, ns)
Maximum Time Interval Error.

    Parameters
    ----------
    data: np.array
        Input data. Provide either phase or frequency (fractional,
        adimensional).
    rate: float
        The sampling rate for data, in Hz. Defaults to 1.0
    data_type: {'phase', 'freq'}
        Data type, i.e. phase or frequency. Defaults to "phase".
    taus: np.array
        Array of tau values, in seconds, for which to compute statistic.
        Optionally set taus=["all"|"octave"|"decade"] for automatic
        tau-list generation.

    Notes
    -----
    this seems to correspond to Stable32 setting "Fast(u)"
    Stable32 also has "Decade" and "Octave" modes where the
    dataset is extended somehow?