code: def median1d(self, param, return_errors=False):
          
          v = [self.mergers[m].median1d(param, return_errors=return_errors) for m in self.mergers]
          if return_errors:
              value, merror, perror = zip(*v)
              return numpy.array(value), numpy.array(merror), numpy.array(perror)
          else:
              return numpy.array(v)
docs: Return median 1d marginalized parameters
  
          Parameters
          ----------
          name: str
              The name of the parameter requested
          return_errors: Optional, {bool, False}
              If true, return a second and third parameter that represents the
              lower and upper 90% error on the parameter.
  
          Returns
          -------
          param: nump.ndarray or tuple
              The requested parameter