code: def fit_naa(self, reject_outliers=3.0, fit_lb=1.8, fit_ub=2.4,
                   phase_correct=True):
          
          model, signal, params = ana.fit_lorentzian(self.diff_spectra,
                                                     self.f_ppm,
                                                     lb=fit_lb,
                                                     ub=fit_ub)
  
          # Store the params:
          self.naa_model = model
          self.naa_signal = signal
          self.naa_params = params
          self.naa_idx = ut.make_idx(self.f_ppm, fit_lb, fit_ub)
          mean_params = stats.nanmean(params, 0)
          self.naa_auc = self._calc_auc(ut.lorentzian, params, self.naa_idx)
docs: Fit a Lorentzian function to the NAA peak at ~ 2 ppm.  Example of
          fitting inverted peak: Foerster et al. 2013, An imbalance between
          excitatory and inhibitory neurotransmitters in amyothrophic lateral
          sclerosis revealed by use of 3T proton MRS