code: def measures(dirnames, measure_func, t_steady=None):
      
      measures, measure_errs = [], []
      for dirname in dirnames:
          meas, meas_err = get_average_measure(dirname, measure_func, t_steady)
          measures.append(meas)
          measure_errs.append(meas_err)
      return np.array(measures), np.array(measure_errs)
docs: Calculate a measure of a set of model output directories,
      for a measure function which returns an associated uncertainty.
  
      Parameters
      ----------
      dirnames: list[str]
          Model output directory paths.
      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.
          The measure will be averaged over all later times.
          `None` means just consider the latest time.
  
      Returns
      -------
      measures: numpy.ndarray
          Measures.
      measure_errs: numpy.ndarray
          Uncertainties.