docs: def fermion_avg(efermi, norm_hopping, func):
      """calcules for every slave it's average over the desired observable"""
      if func == 'ekin':
          func = bethe_ekin_zeroT
      elif func == 'ocupation':
          func = bethe_filling_zeroT
  
      return np.asarray([func(ef, tz) for ef, tz in zip(efermi, norm_hopping)])