def test_unigram_train_smoothed(self):
unigram_model = UnigramModel(UnigramTests.train_str)
unigram_model._calc_probs()
# test one of the probability calculations
# For character 'z'
prob_test = log10(
(1.0 + UnigramModel.SMOOTHING_DEFAULT) /
(len(UnigramTests.train_str) +
UnigramModel.SMOOTHING_DEFAULT * len(unigram_model.char_dict)))
self.assertAlmostEqual(unigram_model.probs_dict['z'],
prob_test,
places=2)
def test_prob(self):
train_str_unique = UnigramTests.str_unique_chars(
UnigramTests.train_str)
unigram_model = UnigramModel(UnigramTests.train_str, smoothing=0.0)
self.assertEqual(len(unigram_model.char_dict), len(train_str_unique))
unigram_model._calc_probs()
# test one of the probability calculations
# For character 'z'
prob_test = log10(1.0 / len(UnigramTests.train_str))
self.assertAlmostEqual(unigram_model.probs_dict['z'],
prob_test,
places=2)
def train_models(training_files):
unigrams = {}
bigrams = {}
for language, documents in training_files.items():
unigram = UnigramModel(smoothing=0.5)
bigram = BigramModel(user_smoothing=0.5)
for document in documents:
text = load_file(DATA_PATH + language + "/" + document)
unigram.train(text)
bigram.train(text)
unigrams[language] = unigram
bigrams[language] = bigram
return unigrams, bigrams
def test_unigram_test_str_smooth(self):
unigram_model = UnigramModel(UnigramTests.train_str)
test_sentence_op = unigram_model.get_string_prob(
UnigramTests.input_str)
total_prob_exp = 0.0
cumul_prob_exp = []
single_prob_exp = {}
char_dict = dict()
char_dict.update(unigram_model.char_dict)
for char in UnigramTests.input_str:
char_dict[char] = 0
for char in UnigramTests.input_str:
if char in unigram_model.char_dict:
current_prob = UnigramModel.calc_prob(
char_count=unigram_model.char_dict[char],
total_count=unigram_model.training_size,
smoothing=UnigramModel.SMOOTHING_DEFAULT,
vocab_size=len(char_dict))
else:
current_prob = UnigramModel.calc_prob(
char_count=0,
total_count=unigram_model.training_size,
smoothing=UnigramModel.SMOOTHING_DEFAULT,
vocab_size=len(char_dict))
single_prob_exp[char] = current_prob
total_prob_exp += current_prob
cumul_prob_exp.append((char, total_prob_exp))
self.assertEqual(len(char_dict), len(unigram_model.char_dict))
self.assertEqual(len(unigram_model.probs_dict),
len(unigram_model.char_dict))
self.assertAlmostEqual(test_sentence_op[0], total_prob_exp, places=2)
self.assertEqual(single_prob_exp, test_sentence_op[1])
self.assertEqual(cumul_prob_exp, test_sentence_op[2])
def test_unigram_test_str(self):
unigram_model = UnigramModel(UnigramTests.train_str, smoothing=0.0)
test_sentence_op = unigram_model.get_string_prob(
UnigramTests.input_str)
self.assertEqual(len(unigram_model.probs_dict),
len(unigram_model.char_dict))
total_prob_exp = 0.0
cumul_prob_exp = []
single_prob_exp = {}
for char in UnigramTests.input_str:
if char in unigram_model.probs_dict:
current_prob = UnigramModel.calc_prob(
char_count=unigram_model.char_dict[char],
total_count=unigram_model.training_size)
total_prob_exp += current_prob
cumul_prob_exp.append((char, total_prob_exp))
single_prob_exp[char] = current_prob
self.assertAlmostEqual(test_sentence_op[0], total_prob_exp, places=2)
self.assertEqual(single_prob_exp, test_sentence_op[1])
self.assertEqual(cumul_prob_exp, test_sentence_op[2])
def test_train(self):
train_str_unique = UnigramTests.str_unique_chars(
UnigramTests.train_str)
unigram_model = UnigramModel(UnigramTests.train_str)
self.assertEqual(len(unigram_model.char_dict), len(train_str_unique))
total_count = 0
for char_count in unigram_model.char_dict.values():
total_count += char_count
self.assertEqual(total_count, len(UnigramTests.train_str))
self.assertTrue(unigram_model.trained)
def test_unigram_test_str_untrained(self):
unigram_model = UnigramModel(smoothing=0.0)
unigram_model_smooth = UnigramModel()
test_sentence_op = unigram_model.get_string_prob(
UnigramTests.input_str)
test_sentence_op_smooth = unigram_model_smooth.get_string_prob(
UnigramTests.input_str)
self.assertAlmostEqual(0.0, test_sentence_op[0], places=2)
self.assertAlmostEqual(0.0, test_sentence_op_smooth[0], places=2)
self.assertEqual({}, test_sentence_op[1])
self.assertEqual({}, test_sentence_op_smooth[1])
self.assertEqual([], test_sentence_op[2])
self.assertEqual([], test_sentence_op_smooth[2])