def lexicon_entry_for(self, token: Token) -> LexiconEntry:
"""
Entry in lexicon that best matches ``token``.
"""
result = None
lexicon_size = len(self.entries)
lexicon_entry_index = 0
best_matching = 0.0
while lexicon_entry_index < lexicon_size and not tools.is_close(best_matching, 1.0):
lexicon_entry = self.entries[lexicon_entry_index]
matching = lexicon_entry.matching(token)
if matching > best_matching:
result = lexicon_entry
best_matching = matching
lexicon_entry_index += 1
return result
def test_can_match_exact_lexicon_entry(nlp_en: Language):
chicken_token = _token_for(nlp_en, _CHICKEN)
chicken_entry = analysis.LexiconEntry(_CHICKEN, RestaurantTopic.FOOD)
assert tools.is_close(chicken_entry.matching(chicken_token), 1.0)
def test_can_detect_close_float_numbers():
assert tools.is_close(0.0, 0.0)
assert tools.is_close(1.0, 1.0)
assert not tools.is_close(1.0, 0.99)
