code: def update_mean_fit_box(self):
          
          self.mean_fit_box.Clear()
          # update high level mean fit box
          fit_index = None
          if self.mean_fit in self.all_fits_list:
              fit_index = self.all_fits_list.index(self.mean_fit)
          self.all_fits_list = []
          for specimen in self.specimens:
              if specimen in self.pmag_results_data['specimens']:
                  for name in [x.name for x in self.pmag_results_data['specimens'][specimen]]:
                      if name not in self.all_fits_list:
                          self.all_fits_list.append(name)
          self.mean_fit_box.SetItems(['None', 'All'] + self.all_fits_list)
          # select defaults
          if not isinstance(fit_index, type(None)):
              self.mean_fit_box.SetValue(self.all_fits_list[fit_index])
          elif self.mean_fit == 'All':
              self.mean_fit_box.SetValue('All')
          else:
              self.mean_fit_box.SetValue('None')
              self.mean_type_box.SetValue('None')
              self.clear_high_level_pars()
          self.update_toggleable_means_menu()
          if self.ie_open:
              self.ie.mean_fit_box.Clear()
              self.ie.mean_fit_box.SetItems(['None', 'All'] + self.all_fits_list)
              if fit_index:
                  self.ie.mean_fit_box.SetValue(self.all_fits_list[fit_index])
              elif self.mean_fit == 'All':
                  self.ie.mean_fit_box.SetValue('All')
              else:
                  self.ie.mean_fit_box.SetValue('None')
                  self.ie.mean_type_box.SetValue('None')
docs: alters mean_fit_box list to match with changes in specimen or new/
          removed interpretations
  
          Alters
          ------
          mean_fit_box selection and choices, mean_types_box string selection