How to use the pyulog.ULog function in pyulog

def open_file(arq):

    class dados:
        class param:
            pass
    # Carrega Mensagens
    msg=['vehicle_attitude','vehicle_attitude_setpoint','actuator_controls_0','vehicle_rates_setpoint'];

    ulog = pyulog.ULog(arq, msg)

    dados.param.r_r_p=ulog.initial_parameters['MC_ROLLRATE_P']
    dados.param.r_r_i=ulog.initial_parameters['MC_ROLLRATE_I']
    dados.param.r_r_d=ulog.initial_parameters['MC_ROLLRATE_D']

    dados.param.r_p_p=ulog.initial_parameters['MC_PITCHRATE_P']
    dados.param.r_p_i=ulog.initial_parameters['MC_PITCHRATE_I']
    dados.param.r_p_d=ulog.initial_parameters['MC_PITCHRATE_D']

    dados.param.r_y_p=ulog.initial_parameters['MC_YAWRATE_P']
    dados.param.r_y_i=ulog.initial_parameters['MC_YAWRATE_I']
    dados.param.r_y_d=ulog.initial_parameters['MC_YAWRATE_D']

    dados.param.a_r_p=ulog.initial_parameters['MC_ROLL_P']
    dados.param.a_p_p=ulog.initial_parameters['MC_PITCH_P']
    dados.param.a_y_p=ulog.initial_parameters['MC_YAW_P']

def read_ulog(ulog_filename, messages=None):
    """
    Convert ulog to pandas dataframe.
    """
    log = pyulog.ULog(ulog_filename, messages)

    # column naming
    d_col_rename = {
        '[': '_',
        ']': '_',
        '.': '_',
    }
    col_rename_pattern = re.compile(
        r'(' + '|'.join([
                            re.escape(key)
                            for key in d_col_rename.keys()]) + r')')

    data = {}
    for msg in log.data_list:
        msg_data = pd.DataFrame.from_dict(msg.data)
        msg_data.columns = [

def open_file(arq):

    class dados:
        class param:
            pass
    # Carrega Mensagens
    msg=['vehicle_attitude','vehicle_attitude_setpoint','actuator_controls_0','vehicle_rates_setpoint'];

    ulog = pyulog.ULog(arq, msg)

    dados.param.r_r_p=ulog.initial_parameters['MC_ROLLRATE_P']
    dados.param.r_r_i=ulog.initial_parameters['MC_ROLLRATE_I']
    dados.param.r_r_d=ulog.initial_parameters['MC_ROLLRATE_D']

    dados.param.r_p_p=ulog.initial_parameters['MC_PITCHRATE_P']
    dados.param.r_p_i=ulog.initial_parameters['MC_PITCHRATE_I']
    dados.param.r_p_d=ulog.initial_parameters['MC_PITCHRATE_D']

    dados.param.r_y_p=ulog.initial_parameters['MC_YAWRATE_P']
    dados.param.r_y_i=ulog.initial_parameters['MC_YAWRATE_I']
    dados.param.r_y_d=ulog.initial_parameters['MC_YAWRATE_D']

    dados.param.a_r_p=ulog.initial_parameters['MC_ROLL_P']
    dados.param.a_p_p=ulog.initial_parameters['MC_PITCH_P']
    dados.param.a_y_p=ulog.initial_parameters['MC_YAW_P']

def process_logdata_ekf(
        filename: str, check_level_dict_filename: str, check_table_filename: str,
        plot: bool = True, sensor_safety_margins: bool = True):

    ## load the log and extract the necessary data for the analyses
    try:
        ulog = ULog(filename)
    except:
        raise PreconditionError('could not open {:s}'.format(filename))

    try:
        # get the dictionary of fail and warning test thresholds from a csv file
        with open(check_level_dict_filename, 'r') as file:
            reader = csv.DictReader(file)
            check_levels = {row['check_id']: float(row['threshold']) for row in reader}
        print('Using test criteria loaded from {:s}'.format(check_level_dict_filename))
    except:
        raise PreconditionError('could not find {:s}'.format(check_level_dict_filename))

    in_air_margin = 5.0 if sensor_safety_margins else 0.0
    # perform the ekf analysis
    master_status, check_status, metrics, airtime_info = analyse_ekf(
        ulog, check_levels, red_thresh=1.0, amb_thresh=0.5, min_flight_duration_seconds=5.0,