X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/1115705cbcf6b3a6ae0f78ed09aa07bf4c1a72ca..3c32c0354ab20d9001f007b29de032659b5c9c84:/nominatim/api/search/geocoder.py?ds=sidebyside diff --git a/nominatim/api/search/geocoder.py b/nominatim/api/search/geocoder.py index f88bffbd..bb3c6a1c 100644 --- a/nominatim/api/search/geocoder.py +++ b/nominatim/api/search/geocoder.py @@ -7,13 +7,15 @@ """ Public interface to the search code. """ -from typing import List, Any, Optional, Iterator, Tuple +from typing import List, Any, Optional, Iterator, Tuple, Dict import itertools +import re import datetime as dt +import difflib from nominatim.api.connection import SearchConnection from nominatim.api.types import SearchDetails -from nominatim.api.results import SearchResults, add_result_details +from nominatim.api.results import SearchResult, SearchResults, add_result_details from nominatim.api.search.token_assignment import yield_token_assignments from nominatim.api.search.db_search_builder import SearchBuilder, build_poi_search, wrap_near_search from nominatim.api.search.db_searches import AbstractSearch @@ -73,42 +75,89 @@ class ForwardGeocoder: is found. """ log().section('Execute database searches') - results = SearchResults() + results: Dict[Any, SearchResult] = {} + end_time = dt.datetime.now() + self.timeout - num_results = 0 - min_ranking = 1000.0 + min_ranking = searches[0].penalty + 2.0 prev_penalty = 0.0 for i, search in enumerate(searches): if search.penalty > prev_penalty and (search.penalty > min_ranking or i > 20): break log().table_dump(f"{i + 1}. Search", _dump_searches([search], query)) - for result in await search.lookup(self.conn, self.params): - results.append(result) - min_ranking = min(min_ranking, result.ranking + 0.5, search.penalty + 0.3) - log().result_dump('Results', ((r.accuracy, r) for r in results[num_results:])) - num_results = len(results) + lookup_results = await search.lookup(self.conn, self.params) + for result in lookup_results: + rhash = (result.source_table, result.place_id, + result.housenumber, result.country_code) + prevresult = results.get(rhash) + if prevresult: + prevresult.accuracy = min(prevresult.accuracy, result.accuracy) + else: + results[rhash] = result + min_ranking = min(min_ranking, result.accuracy * 1.2) + log().result_dump('Results', ((r.accuracy, r) for r in lookup_results)) prev_penalty = search.penalty if dt.datetime.now() >= end_time: break + return SearchResults(results.values()) + + + 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 = min(r.rank_search for r in results) - + min_rank = results[0].rank_search results = SearchResults(r for r in results if r.ranking + 0.05 * (r.rank_search - min_rank) < min_ranking + 0.5) - results.sort(key=lambda r: r.accuracy - r.calculated_importance()) results = SearchResults(results[:self.limit]) return results + def rerank_by_query(self, query: QueryStruct, results: SearchResults) -> None: + """ Adjust the accuracy of the localized result according to how well + they match the original query. + """ + assert self.query_analyzer is not None + qwords = [word for phrase in query.source + for word in re.split('[, ]+', phrase.text) if word] + if not qwords: + return + + for result in results: + # Negative importance indicates ordering by distance, which is + # more important than word matching. + if not result.display_name\ + or (result.importance is not None and result.importance < 0): + continue + distance = 0.0 + norm = self.query_analyzer.normalize_text(result.display_name) + words = set((w for w in norm.split(' ') if w)) + if not words: + continue + for qword in qwords: + wdist = max(difflib.SequenceMatcher(a=qword, b=w).quick_ratio() for w in words) + if wdist < 0.5: + distance += len(qword) + else: + distance += (1.0 - wdist) * len(qword) + # Compensate for the fact that country names do not get a + # match penalty yet by the tokenizer. + # Temporary hack that needs to be removed! + if result.rank_address == 4: + distance *= 2 + result.accuracy += distance * 0.4 / sum(len(w) for w in qwords) + + async def lookup_pois(self, categories: List[Tuple[str, str]], phrases: List[Phrase]) -> SearchResults: """ Look up places by category. If phrase is given, a place search @@ -123,13 +172,16 @@ class ForwardGeocoder: if query: searches = [wrap_near_search(categories, s) for s in searches[:50]] results = await self.execute_searches(query, searches) + 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) else: results = SearchResults() else: search = build_poi_search(categories, self.params.countries) results = await search.lookup(self.conn, self.params) + await add_result_details(self.conn, results, self.params) - await add_result_details(self.conn, results, self.params) log().result_dump('Final Results', ((r.accuracy, r) for r in results)) return results @@ -150,6 +202,10 @@ class ForwardGeocoder: # Execute SQL until an appropriate result is found. results = await self.execute_searches(query, searches[:50]) 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) + log().result_dump('Results after reranking', ((r.accuracy, r) for r in results)) + results = self.sort_and_cut_results(results) log().result_dump('Final Results', ((r.accuracy, r) for r in results)) return results