docs: def compute_absolute_error(self, predicted_data, record, dataframe_record):
          '''Calculate the absolute error for the analysis cases. Must be called after get_experimental_ddg_values.'''
  
          new_idxs = []
          for analysis_set in self.get_analysis_sets(record):
              ddg_details = record['DDG'][analysis_set]
              exp_ddg_fieldname = BenchmarkRun.get_analysis_set_fieldname('Experimental', analysis_set)
              absolute_error_fieldname = BenchmarkRun.get_analysis_set_fieldname('AbsoluteError', analysis_set)
              new_idxs.append(absolute_error_fieldname)
              dataframe_record[absolute_error_fieldname] = None
  
              if ddg_details and predicted_data[self.ddg_analysis_type] != None:
                  absolute_error = abs(dataframe_record[exp_ddg_fieldname] - predicted_data[self.ddg_analysis_type])
                  dataframe_record[absolute_error_fieldname] = absolute_error
  
          # Update the CSV headers
          try:
              idx = self.csv_headers.index('AbsoluteError')
              self.csv_headers = self.csv_headers[:idx] + new_idxs + self.csv_headers[idx + 1:]
          except ValueError, e: pass