docs: def get_high_level_mean_pars(self, high_level_type, high_level_name, calculation_type, elements_type, mean_fit, dirtype):
          """
          Gets the Parameters of a mean of lower level data such as a Site
          level Fisher mean of Specimen interpretations
  
          Parameters
          ----------
          high_level_type : 'samples','sites','locations','study'
          high_level_name : sample, site, location, or study whose
              data to which to apply the mean
          calculation_type : 'Bingham','Fisher','Fisher by polarity'
          elements_type : what to average: 'specimens', 'samples',
              'sites' (Ron. ToDo allow VGP and maybe locations?)
          mean_fit : name of interpretation to average if All uses all
              figure out what level to average,and what elements to average
              (specimen, samples, sites, vgp)
          """
  
          elements_list = self.Data_hierarchy[high_level_type][high_level_name][elements_type]
          pars_for_mean = {}
          pars_for_mean["All"] = []
  
          for element in elements_list:
              if elements_type == 'specimens' and element in self.pmag_results_data['specimens']:
                  for fit in self.pmag_results_data['specimens'][element]:
                      if fit in self.bad_fits:
                          continue
                      if fit.name not in list(pars_for_mean.keys()):
                          pars_for_mean[fit.name] = []
                      try:
                          # is this fit to be included in mean
                          if mean_fit == 'All' or mean_fit == fit.name:
                              pars = fit.get(dirtype)
                              if pars == {} or pars == None:
                                  pars = self.get_PCA_parameters(
                                      element, fit, fit.tmin, fit.tmax, dirtype, fit.PCA_type)
                                  if pars == {} or pars == None:
                                      print(("cannot calculate parameters for element %s and fit %s in calculate_high_level_mean leaving out of fisher mean, please check this value." % (
                                          element, fit.name)))
                                      continue
                                  fit.put(element, dirtype, pars)
                          else:
                              continue
                          if "calculation_type" in list(pars.keys()) and pars["calculation_type"] == 'DE-BFP':
                              dec, inc, direction_type = pars["specimen_dec"], pars["specimen_inc"], 'p'
                          elif "specimen_dec" in list(pars.keys()) and "specimen_inc" in list(pars.keys()):
                              dec, inc, direction_type = pars["specimen_dec"], pars["specimen_inc"], 'l'
                          elif "dec" in list(pars.keys()) and "inc" in list(pars.keys()):
                              dec, inc, direction_type = pars["dec"], pars["inc"], 'l'
                          else:
                              print(
                                  ("-E- ERROR: can't find mean for specimen interpertation: %s , %s" % (element, fit.name)))
                              print(pars)
                              continue
                          # add for calculation
                          pars_for_mean[fit.name].append({'dec': float(dec), 'inc': float(
                              inc), 'direction_type': direction_type, 'element_name': element})
                          pars_for_mean["All"].append({'dec': float(dec), 'inc': float(
                              inc), 'direction_type': direction_type, 'element_name': element})
                      except KeyError:
                          print(
                              ("KeyError in calculate_high_level_mean for element: " + str(element)))
                          continue
              else:
                  try:
                      pars = self.high_level_means[elements_type][element][mean_fit][dirtype]
                      if "dec" in list(pars.keys()) and "inc" in list(pars.keys()):
                          dec, inc, direction_type = pars["dec"], pars["inc"], 'l'
                      else:
                          #                            print "-E- ERROR: can't find mean for element %s"%element
                          continue
                  except KeyError:
                      #                        print("KeyError in calculate_high_level_mean for element: " + str(element) + " please report to a dev")
                      continue
  
          return pars_for_mean