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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def measures(dirnames, measure_func, t_steady=None):
 """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. """

    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)