def test_reader__vectorize_empty(self):
"""Check vectorize method on the empty"""
reader = DSReader(dataset_empty_path)
reader.make_dictionary()
X, y = reader.vectorize()
self.assertEqual([], X.tolist())
self.assertEqual([], y.tolist())
def test_reader__split_test_and_train_data_zero_size(self):
"""Check split_test_and_train_data method with argument size equals to zero"""
reader = DSReader(dataset_split_path)
reader.make_dictionary()
X, y = reader.vectorize()
percent = 0
with self.assertRaises(Exception):
X_train, y_train, X_test, y_test = reader.split_train_and_test(
X, y, percent)
def test_reader__split_test_and_train_data_empty(self):
"""Check split_test_and_train_data method on the empty dataset"""
reader = DSReader(dataset_empty_path)
reader.make_dictionary()
X, y = reader.vectorize()
percent = 0.7
with self.assertRaises(Exception):
X_train, y_train, X_test, y_test = reader.split_train_and_test(
X, y, percent)
def test_reader__split_test_and_train_data(self):
"""Check split_test_and_train_data method"""
reader = DSReader(dataset_split_path)
reader.make_dictionary()
X, y = reader.vectorize()
percent = 0.7
X_train, y_train, X_test, y_test = reader.split_train_and_test(
X, y, percent)
self.assertEqual(X_train.shape[0], X.shape[0] * percent)
self.assertEqual(X_test.shape[0], X.shape[0] * round(1 - percent, 2))
self.assertEqual(y_train.shape[0], y.shape[0] * percent)
self.assertEqual(y_test.shape[0], y.shape[0] * round(1 - percent, 2))
def test_reader__vectorize(self):
"""Check vectorize method"""
x_result = [
[
'During this webinar we will cover what is DevOps and Cloud Native'
], ['New webinar came up'],
[
'During this webinar we will cover what is DevOps and Cloud Native and storage'
]
]
y_result = [1, 1, 0]
reader = DSReader(dataset_path)
reader.make_dictionary()
X, y = reader.vectorize()
for i, row in enumerate(X):
self.assertEqual(x_result[i], row.tolist())
self.assertEqual(y_result, y.tolist())
# my_dataset.remove_stopwords()
# print(my_dataset.dataset)
my_dataset1 = DSReader('C:/Users/Masquerade/Downloads/emails.csv')
my_dataset1.to_lower()
my_dataset1.remove_digits()
my_dataset1.remove_punctuation_marks()
my_dataset1.remove_duplicates()
my_dataset1.remove_stopwords()
my_dataset1.remove_stopwords()
# print(my_dataset1.dataset)
list_email, list_label = my_dataset1.vectorize()
print(list_email.shape)
print(list_label.shape)
X, y = list_email, list_label
# X, y = my_dataset1.dataset.email, my_dataset1.dataset.label
X_train, X_test, y_train, y_test = train_test_split(X.values, y.values)
print("______________________________________________")
print(y_test)
print("______________________________________________")
vectorizer = CountVectorizer()
counts = vectorizer.fit_transform(X_train.ravel())
print("______________________________________________")