def test_probability_language_detector_calls_required_method(self, mock):
unknown_file = open('lab_3/unknown_Arthur_Conan_Doyle.txt', encoding='utf-8')
german_file = open('lab_3/Thomas_Mann.txt', encoding='utf-8')
english_file = open('lab_3/Frank_Baum.txt', encoding='utf-8')
text_unk = tokenize_by_sentence(unknown_file.read())
text_ger = tokenize_by_sentence(german_file.read())
text_eng = tokenize_by_sentence(english_file.read())
english_file.close()
german_file.close()
unknown_file.close()
letter_storage = LetterStorage()
letter_storage.update(text_eng)
letter_storage.update(text_ger)
letter_storage.update(text_unk)
eng_encoded = encode_corpus(letter_storage, text_eng)
unk_encoded = encode_corpus(letter_storage, text_unk)
ger_encoded = encode_corpus(letter_storage, text_ger)
language_detector = ProbabilityLanguageDetector((3, 4, 5), 1000)
language_detector.new_language(eng_encoded, 'english')
language_detector.new_language(ger_encoded, 'german')
ngram_unknown = NGramTrie(4)
ngram_unknown.fill_n_grams(unk_encoded)
language_detector.detect_language(ngram_unknown.n_grams)
self.assertTrue(mock.called)
def test_probability_language_detector_detect_language_ideal(self):
unknown_file = open('lab_3/unknown_Arthur_Conan_Doyle.txt',
encoding='utf-8')
german_file = open('lab_3/Thomas_Mann.txt', encoding='utf-8')
english_file = open('lab_3/Frank_Baum.txt', encoding='utf-8')
text_unk = tokenize_by_sentence(unknown_file.read())
text_ger = tokenize_by_sentence(german_file.read())
text_eng = tokenize_by_sentence(english_file.read())
english_file.close()
german_file.close()
unknown_file.close()
letter_storage = LetterStorage()
letter_storage.update(text_eng)
letter_storage.update(text_ger)
letter_storage.update(text_unk)
eng_encoded = encode_corpus(letter_storage, text_eng)
unk_encoded = encode_corpus(letter_storage, text_unk)
ger_encoded = encode_corpus(letter_storage, text_ger)
language_detector = ProbabilityLanguageDetector((3, 4, 5), 1000)
language_detector.new_language(eng_encoded, 'english')
language_detector.new_language(ger_encoded, 'german')
actual = language_detector.detect_language(unk_encoded)
self.assertTrue(actual['german'] > actual['english'])
def test_probability_language_detector_detect_incorrect(self):
language_detector = ProbabilityLanguageDetector((3, 5), 100)
bad_inputs = [[], {}, '', 1, None, True, (None,)]
expected = {}
for bad_input in bad_inputs:
actual = language_detector.detect_language(bad_input)
self.assertEqual(expected, actual)
text_unk = tokenize_by_sentence(unknown_file.read())
text_ger = tokenize_by_sentence(german_file.read())
text_eng = tokenize_by_sentence(english_file.read())
english_file.close()
german_file.close()
unknown_file.close()
letter_storage = LetterStorage()
letter_storage.update(text_eng)
letter_storage.update(text_ger)
letter_storage.update(text_unk)
eng_encoded = encode_corpus(letter_storage, text_eng)
unk_encoded = encode_corpus(letter_storage, text_unk)
ger_encoded = encode_corpus(letter_storage, text_ger)
language_detector = ProbabilityLanguageDetector((3, 4, 5), 1000)
language_detector.new_language(eng_encoded, 'english')
language_detector.new_language(ger_encoded, 'german')
ngram_unknown = NGramTrie(4)
ngram_unknown.fill_n_grams(unk_encoded)
actual = language_detector.detect_language(ngram_unknown.n_grams)
print(actual)
RESULT = actual['english'] < actual['german']
# DO NOT REMOVE NEXT LINE - KEEP IT INTENTIONALLY LAST
assert RESULT == 1, ''
