"""
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
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
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])
+ 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()))
if self.details.categories:
return dbf.WeightedCategories(self.details.categories,