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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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)