def _apply_best_spans_to_primaries(self):
self.smooth_result = []<EOL>for xi, best_span in enumerate(self._smoothed_best_spans.smooth_result):<EOL><INDENT>primary_values = [s.smooth_result[xi] for s in self._primary_smooths]<EOL>best_value = numpy.interp(best_span, DEFAULT_SPANS, primary_values)<EOL>self.smooth_result.append(best_value)<EOL><DEDENT>
Apply best spans.

Given the best span, interpolate to compute the best smoothed value
at each observation.