code: def return_nearest_cutoff(name, mass_dict, freqs):
      
      # A bypass for the redundant case
      if len(freqs) == 1:
          return numpy.zeros(len(mass_dict['m1']), dtype=float) + freqs[0]
      cutoff_fns = pnutils.named_frequency_cutoffs
      if name not in cutoff_fns.keys():
          err_msg = "%s not recognized as a valid cutoff frequency choice." %name
          err_msg += "Recognized choices: " + " ".join(cutoff_fns.keys())
          raise ValueError(err_msg)
      f_cutoff = cutoff_fns[name](mass_dict)
      return find_closest_calculated_frequencies(f_cutoff, freqs)
docs: Given an array of total mass values and an (ascending) list of
      frequencies, this will calculate the specified cutoff formula for each
      mtotal and return the nearest frequency to each cutoff from the input
      list.
      Currently only supports cutoffs that are functions of the total mass
      and no other parameters (SchwarzISCO, LightRing, ERD)
  
      Parameters
      ----------
      name : string
          Name of the cutoff formula to be approximated
      mass_dict : Dictionary where the keys are used to call the functions
          returned by tmpltbank.named_frequency_cutoffs. The values can be
          numpy arrays or single values.
      freqs : list of floats
          A list of frequencies (must be sorted ascending)
  
      Returns
      -------
      numpy.array
          The frequencies closest to the cutoff for each value of totmass.