<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def query(self, s):
 """Query the search index for sets similar to the query set. Args: s (Iterable):
 the query set. Returns (list):
 a list of tuples `(index, similarity)` where the index is the index of the matching sets in the original list of sets. """

        s1 = np.sort([self.order[token] for token in s if token in self.order])
        logging.debug("{} original tokens and {} tokens after applying "
            "frequency order.".format(len(s), len(s1)))
        prefix = self._get_prefix(s1)
        candidates = set([i for p1, token in enumerate(prefix)
                for i, p2 in self.index[token]
                if self.position_filter_func(s1, self.sets[i], p1, p2,
                    self.similarity_threshold)])
        logging.debug("{} candidates found.".format(len(candidates)))
        results = deque([])
        for i in candidates:
            s2 = self.sets[i]
            sim = self.similarity_func(s1, s2)
            if sim < self.similarity_threshold:
                continue
            results.append((i, sim))
        logging.debug("{} verified sets found.".format(len(results)))
        return list(results)