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c417b6f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | import unittest
import os
import shutil
import pickle
import pandas as pd
from sklearn.linear_model import LinearRegression
from model_testing import test_model
class TestModelTesting(unittest.TestCase):
def setUp(self):
# Create a temporary directory
self.temp_dir = 'temp_test'
os.mkdir(self.temp_dir)
# Create temporary test data directory
self.test_data_dir = os.path.join(self.temp_dir, 'data')
os.mkdir(self.test_data_dir)
# Create temporary test data with the required pattern
test_features = pd.DataFrame({
'open': [0.6095, 0.5759, 0.6418],
'high': [0.6112, -0.7703, 0.13523],
'low': [1.7676, 0.23695, 0.6469],
'close': [1.0887, 0.4828, 2.657],
'volume': [-0.10299, 1.173, 1.345]
})
test_target = pd.Series([1.624, 2.223, 0.064], name='target')
test_features.to_csv(os.path.join(self.test_data_dir,
'test_features.csv'), index=True)
test_target.to_csv(os.path.join(self.test_data_dir, 'test_target.csv'),
index=True)
# Create a simple linear regression model and save it to a pickle file
model = LinearRegression()
model.fit(test_features, test_target)
with open(os.path.join(self.temp_dir,
'test_model.pkl'), 'wb') as model_file:
pickle.dump(model, model_file)
def tearDown(self):
# Clean up temporary directory and files
shutil.rmtree(self.temp_dir)
def test_test_model(self):
# Call the function with the temporary directory and model path
result = test_model(model_path=os.path.join(self.temp_dir,
'test_model.pkl'),
data_dir=self.test_data_dir)
# Assert that the result is as expected
self.assertTrue("Mean Squared Error:" in result)
self.assertTrue("R-squared:" in result)
if __name__ == '__main__':
unittest.main()
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