]> git.openstreetmap.org Git - nominatim.git/blobdiff - nominatim/api/search/db_search_builder.py
the category parameter in search should result in a qualifier
[nominatim.git] / nominatim / api / search / db_search_builder.py
index 377c4be7da959b156b19d531ab5e1511fc5be515..35d10e782e3d19026de775270c329c4db8dddb2b 100644 (file)
@@ -7,7 +7,7 @@
 """
 Convertion from token assignment to an abstract DB search.
 """
-from typing import Optional, List, Tuple, Iterator
+from typing import Optional, List, Tuple, Iterator, Dict
 import heapq
 
 from nominatim.api.types import SearchDetails, DataLayer
@@ -206,45 +206,33 @@ class SearchBuilder:
 
         partials_indexed = all(t.is_indexed for t in name_partials) \
                            and all(t.is_indexed for t in addr_partials)
-        exp_count = min(t.count for t in name_partials)
+        exp_count = min(t.count for t in name_partials) / (2**(len(name_partials) - 1))
 
-        if (len(name_partials) > 3 or exp_count < 3000) and partials_indexed:
+        if (len(name_partials) > 3 or exp_count < 8000) and partials_indexed:
             yield penalty, exp_count, dbf.lookup_by_names(name_tokens, addr_tokens)
             return
 
-        exp_count = exp_count / (2**len(addr_partials)) if addr_partials else exp_count
-
         # Partial term to frequent. Try looking up by rare full names first.
         name_fulls = self.query.get_tokens(name, TokenType.WORD)
-        rare_names = list(filter(lambda t: t.count < 10000, name_fulls))
+        fulls_count = sum(t.count for t in name_fulls)
         # At this point drop unindexed partials from the address.
         # This might yield wrong results, nothing we can do about that.
         if not partials_indexed:
             addr_tokens = [t.token for t in addr_partials if t.is_indexed]
             penalty += 1.2 * sum(t.penalty for t in addr_partials if not t.is_indexed)
-        if rare_names:
-            # Any of the full names applies with all of the partials from the address
-            yield penalty, sum(t.count for t in rare_names),\
-                  dbf.lookup_by_any_name([t.token for t in rare_names], addr_tokens)
+        # Any of the full names applies with all of the partials from the address
+        yield penalty, fulls_count / (2**len(addr_partials)),\
+              dbf.lookup_by_any_name([t.token for t in name_fulls], addr_tokens,
+                                     'restrict' if fulls_count < 10000 else 'lookup_all')
 
         # To catch remaining results, lookup by name and address
         # We only do this if there is a reasonable number of results expected.
-        if exp_count < 10000:
-            if all(t.is_indexed for t in name_partials):
-                lookup = [dbf.FieldLookup('name_vector', name_tokens, 'lookup_all')]
-            else:
-                # we don't have the partials, try with the non-rare names
-                non_rare_names = [t.token for t in name_fulls if t.count >= 10000]
-                if not non_rare_names:
-                    return
-                lookup = [dbf.FieldLookup('name_vector', non_rare_names, 'lookup_any')]
+        exp_count = exp_count / (2**len(addr_partials)) if addr_partials else exp_count
+        if exp_count < 10000 and all(t.is_indexed for t in name_partials):
+            lookup = [dbf.FieldLookup('name_vector', name_tokens, 'lookup_all')]
             if addr_tokens:
                 lookup.append(dbf.FieldLookup('nameaddress_vector', addr_tokens, 'lookup_all'))
-            penalty += 0.1 * max(0, 5 - len(name_partials) - len(addr_tokens))
-            if len(rare_names) == len(name_fulls):
-                # if there already was a search for all full tokens,
-                # avoid this if anything has been found
-                penalty += 0.25
+            penalty += 0.35 * max(0, 5 - len(name_partials) - len(addr_tokens))
             yield penalty, exp_count, lookup
 
 
@@ -333,8 +321,15 @@ class SearchBuilder:
                               self.query.get_tokens(assignment.postcode,
                                                     TokenType.POSTCODE))
         if assignment.qualifier:
-            sdata.set_qualifiers(self.query.get_tokens(assignment.qualifier,
-                                                       TokenType.QUALIFIER))
+            tokens = self.query.get_tokens(assignment.qualifier, TokenType.QUALIFIER)
+            if self.details.categories:
+                tokens = [t for t in tokens if t.get_category() in self.details.categories]
+                if not tokens:
+                    return None
+            sdata.set_qualifiers(tokens)
+        elif self.details.categories:
+            sdata.qualifiers = dbf.WeightedCategories(self.details.categories,
+                                                      [0.0] * len(self.details.categories))
 
         if assignment.address:
             sdata.set_ranking([self.get_addr_ranking(r) for r in assignment.address])
@@ -351,16 +346,13 @@ class SearchBuilder:
             Returns None if no category search is requested.
         """
         if assignment.category:
-            tokens = [t for t in self.query.get_tokens(assignment.category,
-                                                       TokenType.CATEGORY)
-                      if not self.details.categories
-                         or t.get_category() in self.details.categories]
-            return dbf.WeightedCategories([t.get_category() for t in tokens],
-                                          [t.penalty for t in tokens])
-
-        if self.details.categories:
-            return dbf.WeightedCategories(self.details.categories,
-                                          [0.0] * len(self.details.categories))
+            tokens: Dict[Tuple[str, str], float] = {}
+            for t in self.query.get_tokens(assignment.category, TokenType.CATEGORY):
+                cat = t.get_category()
+                if (not self.details.categories or cat in self.details.categories)\
+                   and t.penalty < tokens.get(cat, 1000.0):
+                    tokens[cat] = t.penalty
+            return dbf.WeightedCategories(list(tokens.keys()), list(tokens.values()))
 
         return None