docs: def get_average_measure(dirname, measure_func, t_steady=None):
      """
      Calculate a measure of a model in an output directory, averaged over
      all times when the model is at steady-state.
  
      Parameters
      ----------
      dirname: str
          Output directory
      measure_func: function
          Function which takes a :class:`Model` instance as a single argument,
          and returns the measure of interest, and its uncertainty.
      t_steady: None or float
          Time to consider the model to be at steady-state.
          `None` means just consider the latest time.
  
      Returns
      -------
      measure: numpy.ndarray
          Measure.
      measure_errs: numpy.ndarray
          Measure uncertainty.
          If no averaging is done, this is taken from the measure_func.
          Otherwise, the standard error over all samples is used.
      """
      if t_steady is None:
          meas, meas_err = measure_func(get_recent_model(dirname))
          return meas, meas_err
      else:
          ms = [filename_to_model(fname) for fname in get_filenames(dirname)]
          ms_steady = [m for m in ms if m.t > t_steady]
          meas_list = [measure_func(m) for m in ms_steady]
          meases, meas_errs = zip(*meas_list)
          return np.mean(meases), sem(meases)