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_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_new_language_storage_already_created(self):
letter_storage = LetterStorage()
language_detector = LanguageDetector((3, ), 10)
file = open('lab_3/Thomas_Mann.txt', 'r', encoding='utf-8')
file_unknown = open('lab_3/unknown_Arthur_Conan_Doyle.txt',
'r',
encoding='utf-8')
text = tokenize_by_sentence(file.read())
text_unknown = tokenize_by_sentence(file_unknown.read())
letter_storage.update(text)
letter_storage.update(text_unknown)
encoded_text = encode_corpus(letter_storage, text)
encoded_unknown_text = encode_corpus(letter_storage, text_unknown)
file.close()
file_unknown.close()
language_detector.new_language(encoded_text, 'german')
language_detector.new_language(encoded_unknown_text, 'english')
self.assertTrue(language_detector.n_gram_storages['german'])
self.assertTrue(language_detector.n_gram_storages['english'])
self.assertEqual(type(language_detector.n_gram_storages['german'][3]),
NGramTrie)
self.assertEqual(type(language_detector.n_gram_storages['english'][3]),
NGramTrie)
def test_detect_language_uses_several_ngrams(self):
letter_storage = LetterStorage()
language_detector = LanguageDetector((2, 3), 100)
file_first = open('lab_3/Frank_Baum.txt', 'r', encoding='utf-8')
file_second = open('lab_3/Thomas_Mann.txt', 'r', encoding='utf-8')
file_third = open('lab_3/unknown_Arthur_Conan_Doyle.txt',
'r',
encoding='utf-8')
text_english = tokenize_by_sentence(file_first.read())
text_german = tokenize_by_sentence(file_second.read())
text_unknown = tokenize_by_sentence(file_third.read())
letter_storage.update(text_english)
letter_storage.update(text_german)
letter_storage.update(text_unknown)
encoded_english = encode_corpus(letter_storage, text_english)
encoded_german = encode_corpus(letter_storage, text_german)
encoded_unknown = encode_corpus(letter_storage, text_unknown)
file_first.close()
file_second.close()
file_third.close()
language_detector.new_language(encoded_english, 'english')
language_detector.new_language(encoded_german, 'german')
actual = language_detector.detect_language(encoded_unknown)
self.assertTrue(actual['german'] > actual['english'])
def test_tokenize_by_sentence_inappropriate_sentence(self):
"""
Tests that tokenize_by_sentence function
can handle inappropriate sentence input
"""
text = '$#&*@#$*#@)'
expected = ()
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_empty_sentence(self):
"""
Tests that tokenize_by_sentence function
can handle empty sentence input
"""
text = ''
expected = ()
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_incorrect_input(self):
"""
Tests that tokenize_by_sentence function
can handle incorrect input cases
"""
bad_inputs = [[], {}, (), None, 9, 9.34, True]
expected = ()
for bad_input in bad_inputs:
actual = tokenize_by_sentence(bad_input)
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_ideal(self):
"""
Tests that tokenize_by_sentence function
can handle ideal two sentence input
"""
text = 'She is happy. He is happy.'
expected = ((('_', 's', 'h', 'e', '_'), ('_', 'i', 's', '_'),
('_', 'h', 'a', 'p', 'p', 'y', '_')),
(('_', 'h', 'e', '_'), ('_', 'i', 's', '_'),
('_', 'h', 'a', 'p', 'p', 'y', '_')))
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
def test_detect_language_calls_required_method(self, mock):
letter_storage = LetterStorage()
language_detector = LanguageDetector((3, ), 10)
text_to_detect = (((1, 2, 3), ), )
file = open('lab_3/Frank_Baum.txt', 'r', encoding='utf-8')
text = tokenize_by_sentence(file.read())
letter_storage.update(text)
encoded_text = encode_corpus(letter_storage, text)
file.close()
language_detector.new_language(encoded_text, 'english')
language_detector.detect_language(text_to_detect)
self.assertTrue(mock.called)
def test_probability_language_detector_calculate_probability_ideal(self):
print('launching test')
english_file = open('lab_3/Frank_Baum.txt', encoding='utf-8')
german_file = open('lab_3/Thomas_Mann.txt', encoding='utf-8')
unknown_file = open('lab_3/unknown_Arthur_Conan_Doyle.txt', encoding='utf-8')
english_text = tokenize_by_sentence(english_file.read())
german_text = tokenize_by_sentence(german_file.read())
unknown_text = tokenize_by_sentence(unknown_file.read())
english_file.close()
german_file.close()
unknown_file.close()
letter_storage = LetterStorage()
letter_storage.update(english_text)
letter_storage.update(german_text)
letter_storage.update(unknown_text)
english_encoded = encode_corpus(letter_storage, english_text)
german_encoded = encode_corpus(letter_storage, german_text)
unknown_encoded = encode_corpus(letter_storage, unknown_text)
language_detector = ProbabilityLanguageDetector((3,), 1000)
language_detector.new_language(english_encoded, 'english')
language_detector.new_language(german_encoded, 'german')
n3_gram_trie_english = language_detector.n_gram_storages['english'][3]
n3_gram_trie_german = language_detector.n_gram_storages['german'][3]
n3_gram_unknown = NGramTrie(3)
n3_gram_unknown.fill_n_grams(unknown_encoded)
english_prob = language_detector._calculate_sentence_probability(n3_gram_trie_english,
n3_gram_unknown.n_grams)
german_prob = language_detector._calculate_sentence_probability(n3_gram_trie_german,
n3_gram_unknown.n_grams)
print(f'English_sentence_prob: {english_prob}')
print(f'Deutsch_sentence_prob: {german_prob}')
self.assertTrue(english_prob > german_prob)
def test_probability_language_detector_several_ngrams_case(self):
language_detector = ProbabilityLanguageDetector((3, 5), 1000)
english_file = open('lab_3/Frank_Baum.txt', encoding='utf-8')
german_file = open('lab_3/Thomas_Mann.txt', encoding='utf-8')
unknown_file = open('lab_3/unknown_Arthur_Conan_Doyle.txt',
encoding='utf-8')
eng_text = tokenize_by_sentence(english_file.read())
ger_text = tokenize_by_sentence(german_file.read())
unk_text = tokenize_by_sentence(unknown_file.read())
english_file.close()
german_file.close()
unknown_file.close()
letter_storage = LetterStorage()
letter_storage.update(eng_text)
letter_storage.update(ger_text)
letter_storage.update(unk_text)
english_encoded = encode_corpus(letter_storage, eng_text)
german_encoded = encode_corpus(letter_storage, ger_text)
unknown_encoded = encode_corpus(letter_storage, unk_text)
language_detector.new_language(english_encoded, 'english')
language_detector.new_language(german_encoded, 'german')
eng_prob = language_detector.n_gram_storages['english'][5]
ger_prob = language_detector.n_gram_storages['german'][5]
ngram_trie = NGramTrie(5)
ngram_trie.fill_n_grams(unknown_encoded)
eng = language_detector._calculate_sentence_probability(
eng_prob, ngram_trie.n_grams)
ger = language_detector._calculate_sentence_probability(
ger_prob, ngram_trie.n_grams)
self.assertTrue(ger > eng)
def test_new_language_creates_several_ngrams(self):
letter_storage = LetterStorage()
language_detector = LanguageDetector((2, 3), 10)
file = open('lab_3/Frank_Baum.txt', 'r', encoding='utf-8')
text = tokenize_by_sentence(file.read())
letter_storage.update(text)
encoded_text = encode_corpus(letter_storage, text)
file.close()
language_detector.new_language(encoded_text, 'english')
self.assertTrue(language_detector.n_gram_storages['english'][2])
self.assertTrue(language_detector.n_gram_storages['english'][3])
def test_new_language_add_existing_language(self):
letter_storage = LetterStorage()
language_detector = LanguageDetector((3, ), 10)
file = open('lab_3/Frank_Baum.txt', 'r', encoding='utf-8')
text = tokenize_by_sentence(file.read())
letter_storage.update(text)
encoded_text = encode_corpus(letter_storage, text)
file.close()
expected = 0
language_detector.new_language(encoded_text, 'german')
actual = language_detector.new_language(encoded_text, 'german')
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_dirty_text(self):
"""
Tests that tokenize_by_sentence function
can handle text filled with inappropriate characters
"""
text = 'The first% sentence><. The sec&*ond sent@ence #.'
expected = ((('_', 't', 'h', 'e', '_'), ('_', 'f', 'i', 'r', 's', 't',
'_'),
('_', 's', 'e', 'n', 't', 'e', 'n', 'c', 'e', '_')),
(('_', 't', 'h', 'e', '_'), ('_', 's', 'e', 'c', 'o', 'n',
'd', '_'),
('_', 's', 'e', 'n', 't', 'e', 'n', 'c', 'e', '_')))
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_punctuation_marks(self):
"""
Tests that tokenize_by_sentence function
can process and ignore different punctuation marks
"""
text = 'The, first sentence - nice. The second sentence: bad!'
expected = ((('_', 't', 'h', 'e', '_'), ('_', 'f', 'i', 'r', 's', 't',
'_'),
('_', 's', 'e', 'n', 't', 'e', 'n', 'c', 'e',
'_'), ('_', 'n', 'i', 'c', 'e', '_')),
(('_', 't', 'h', 'e', '_'), ('_', 's', 'e', 'c', 'o', 'n',
'd', '_'),
('_', 's', 'e', 'n', 't', 'e', 'n', 'c', 'e',
'_'), ('_', 'b', 'a', 'd', '_')))
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
def test_tokenize_by_sentence_complex(self):
"""
Tests that tokenize_by_sentence function
can handle complex split case
"""
text = 'Mar#y wa$nted, to swim. However, she was afraid of sharks.'
expected = ((('_', 'm', 'a', 'r', 'y', '_'), ('_', 'w', 'a', 'n', 't',
'e', 'd', '_'),
('_', 't', 'o', '_'), ('_', 's', 'w', 'i', 'm', '_')),
(('_', 'h', 'o', 'w', 'e', 'v', 'e', 'r', '_'),
('_', 's', 'h', 'e', '_'), ('_', 'w', 'a', 's', '_'),
('_', 'a', 'f', 'r', 'a', 'i', 'd',
'_'), ('_', 'o', 'f', '_'), ('_', 's', 'h', 'a', 'r',
'k', 's', '_')))
actual = tokenize_by_sentence(text)
self.assertEqual(expected, actual)
from lab_3.main import encode_corpus
from lab_3.main import LetterStorage
if __name__ == '__main__':
# here goes your function calls
letter_storage = LetterStorage()
language_detector = LanguageDetector((3, ), 100)
file_first = open('lab_3/Frank_Baum.txt', 'r', encoding='utf-8')
file_second = open('lab_3/Thomas_Mann.txt', 'r', encoding='utf-8')
file_third = open('lab_3/unknown_Arthur_Conan_Doyle.txt',
'r',
encoding='utf-8')
text_english = tokenize_by_sentence(file_first.read())
text_german = tokenize_by_sentence(file_second.read())
text_unknown = tokenize_by_sentence(file_third.read())
letter_storage.update(text_english)
letter_storage.update(text_german)
letter_storage.update(text_unknown)
encoded_english = encode_corpus(letter_storage, text_english)
encoded_german = encode_corpus(letter_storage, text_german)
encoded_unknown = encode_corpus(letter_storage, text_unknown)
file_first.close()
file_second.close()
file_third.close()
language_detector.new_language(encoded_english, 'english')
language_detector.new_language(encoded_german, 'german')
Language detector implementation starter
"""
from lab_3.main import tokenize_by_sentence
from lab_3.main import encode_corpus
from lab_3.main import NGramTrie
from lab_3.main import LetterStorage
from lab_3.main import LanguageDetector
if __name__ == '__main__':
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)
