def get_tdata(t_format, files):
    def median(arr):
        return arr.min() + (arr.max() - arr.min())/2
    import re
    from pandas import Index
    t_pattern = t_format
    for fmt, patt in t_patterns.items():
        t_pattern = t_pattern.replace(fmt, patt)
    t_pattern = re.compile(t_pattern)
    time = list(range(len(files)))
    for i, f in enumerate(files):
        time[i] = median(np.array(list(map(
            lambda s: np.datetime64(dt.datetime.strptime(s, t_format)),
            t_pattern.findall(f)))))
    ind = np.argsort(time)
    files = np.array(files)[ind]
    time = np.array(time)[ind]
    return to_datetime(Index(time, name='time')), files