docs: def _apply_best_spans_to_primaries(self):
          """
          Apply best spans.
  
          Given the best span, interpolate to compute the best smoothed value
          at each observation.
          """
          self.smooth_result = []
          for xi, best_span in enumerate(self._smoothed_best_spans.smooth_result):
              primary_values = [s.smooth_result[xi] for s in self._primary_smooths]
              # pylint: disable=no-member
              best_value = numpy.interp(best_span, DEFAULT_SPANS, primary_values)
              self.smooth_result.append(best_value)