import unittest import import_ipynb import pandas as pd import pandas.testing as pd_testing import numpy.testing as np_testing from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score class Test(unittest.TestCase): def setUp(self): import Exercise4_01 self.exercises = Exercise4_01 self.file_url = '../Dataset/openml_phpZNNasq.csv' self.df = pd.read_csv(self.file_url) self.y = self.df.pop('type') self.df.drop(columns='animal', inplace=True) self.X_train, self.X_test, self.y_train, self.y_test = train_test_split(self.df, self.y, test_size=0.4, random_state=188) self.rf_model = RandomForestClassifier(random_state=42) self.rf_model.fit(self.X_train, self.y_train) self.train_preds = self.rf_model.predict(self.X_train) self.test_preds = self.rf_model.predict(self.X_test) self.train_acc = accuracy_score(self.y_train, self.train_preds) self.test_acc = accuracy_score(self.y_test, self.test_preds) def test_file_url(self): self.assertEqual(self.exercises.file_url, self.file_url) def test_df(self): pd_testing.assert_frame_equal(self.exercises.df, self.df) def test_y(self): np_testing.assert_array_equal(self.exercises.y , self.y) def test_X_train(self): np_testing.assert_array_equal(self.exercises.X_train , self.X_train) def test_X_test(self): np_testing.assert_array_equal(self.exercises.X_test, self.X_test) def test_y_train(self): np_testing.assert_array_equal(self.exercises.y_train , self.y_train) def test_y_test(self): np_testing.assert_array_equal(self.exercises.y_test , self.y_test) def test_train_preds(self): np_testing.assert_array_equal(self.exercises.train_preds , self.train_preds) def test_test_preds(self): np_testing.assert_array_equal(self.exercises.test_preds, self.test_preds) def test_train_acc(self): self.assertEqual(self.exercises.train_acc, self.train_acc) def test_test_acc(self): self.assertEqual(self.exercises.test_acc, self.test_acc) if __name__ == '__main__': unittest.main()