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fenago
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
import unittest
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import import_ipynb
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.pipeline import Pipeline
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from sklearn.linear_model import LinearRegression
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from sklearn.metrics import mean_absolute_error
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from sklearn.preprocessing import MinMaxScaler
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from sklearn.preprocessing import StandardScaler
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from sklearn.preprocessing import PolynomialFeatures
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import pandas.testing as pd_testing
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import numpy.testing as np_testing
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class MyTestCase(unittest.TestCase):
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def setUp(self):
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import Exercise6_04
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self.exercises = Exercise6_04
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self.headers = ['CIC0', 'SM1', 'GATS1i', 'NdsCH', 'Ndssc', 'MLOGP', 'response']
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self.df = pd.read_csv(
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'../Dataset/qsar_fish_toxicity.csv',
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names=self.headers, sep=';')
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self.features = self.df.drop('response', axis=1).values
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self.labels = self.df[['response']].values
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self.X_train, self.X_eval, self.y_train, self.y_eval = train_test_split(self.features, self.labels, test_size=0.2, random_state=0)
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self.X_val, self.X_test, self.y_val, self.y_test = train_test_split(self.X_eval, self.y_eval, random_state=0)
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self.steps = [
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('scaler', MinMaxScaler()),
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('poly', PolynomialFeatures(2)),
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('model', LinearRegression())
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]
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self.model = Pipeline(self.steps)
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self.model.fit(self.X_train, self.y_train)
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self.y_pred = self.model.predict(self.X_val)
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self.mae = mean_absolute_error(self.y_val, self.y_pred)
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self.r2 = self.model.score(self.X_val, self.y_val)
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def test_df(self):
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pd_testing.assert_frame_equal(self.exercises.df, self.df)
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def test_features(self):
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np_testing.assert_array_equal(self.exercises.features, self.features)
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def test_labels(self):
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np_testing.assert_array_equal(self.exercises.labels, self.labels)
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def test_X_train(self):
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np_testing.assert_array_equal(self.exercises.X_train, self.X_train)
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def test_X_val(self):
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np_testing.assert_array_equal(self.exercises.X_val, self.X_val)
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def test_X_test(self):
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np_testing.assert_array_equal(self.exercises.X_test, self.X_test)
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def test_y_train(self):
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np_testing.assert_array_equal(self.exercises.y_train, self.y_train)
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def test_y_val(self):
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np_testing.assert_array_equal(self.exercises.y_val, self.y_val)
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def test_y_test(self):
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np_testing.assert_array_equal(self.exercises.y_test, self.y_test)
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def test_y_pred(self):
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np_testing.assert_array_equal(self.exercises.y_pred, self.y_pred)
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def test_r2(self):
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self.assertEqual(self.exercises.r2, self.r2)
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def test_mae(self):
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self.assertEqual(self.exercises.mae, self.mae)
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if __name__ == '__main__':
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unittest.main()
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