prevresult.accuracy = min(prevresult.accuracy, result.accuracy)
else:
results[rhash] = result
- min_ranking = min(min_ranking, result.accuracy * 1.2)
+ min_ranking = min(min_ranking, result.accuracy * 1.2, 2.0)
log().result_dump('Results', ((r.accuracy, r) for r in lookup_results))
prev_penalty = search.penalty
if dt.datetime.now() >= end_time:
return SearchResults(results.values())
+ def pre_filter_results(self, results: SearchResults) -> SearchResults:
+ """ Remove results that are significantly worse than the
+ best match.
+ """
+ if results:
+ max_ranking = min(r.ranking for r in results) + 0.5
+ results = SearchResults(r for r in results if r.ranking < max_ranking)
+
+ return results
+
+
def sort_and_cut_results(self, results: SearchResults) -> SearchResults:
""" Remove badly matching results, sort by ranking and
limit to the configured number of results.
"""
if results:
- min_ranking = min(r.ranking for r in results)
- results = SearchResults(r for r in results if r.ranking < min_ranking + 0.5)
results.sort(key=lambda r: r.ranking)
-
- if results:
min_rank = results[0].rank_search
+ min_ranking = results[0].ranking
results = SearchResults(r for r in results
- if r.ranking + 0.05 * (r.rank_search - min_rank)
+ if r.ranking + 0.03 * (r.rank_search - min_rank)
< min_ranking + 0.5)
results = SearchResults(results[:self.limit])
if query:
searches = [wrap_near_search(categories, s) for s in searches[:50]]
results = await self.execute_searches(query, searches)
+ results = self.pre_filter_results(results)
await add_result_details(self.conn, results, self.params)
log().result_dump('Preliminary Results', ((r.accuracy, r) for r in results))
results = self.sort_and_cut_results(results)
if searches:
# Execute SQL until an appropriate result is found.
results = await self.execute_searches(query, searches[:50])
+ results = self.pre_filter_results(results)
await add_result_details(self.conn, results, self.params)
log().result_dump('Preliminary Results', ((r.accuracy, r) for r in results))
self.rerank_by_query(query, results)