| import unittest | |
| from result_data_processor import ResultDataProcessor | |
| import pandas as pd | |
| class TestResultDataProcessor(unittest.TestCase): | |
| def setUp(self): | |
| self.processor = ResultDataProcessor() | |
| # check that the result is a pandas dataframe | |
| def test_process_data(self): | |
| data = self.processor.data | |
| self.assertIsInstance(data, pd.DataFrame) | |
| # check that pandas dataframe has the right columns | |
| def test_columns(self): | |
| data = self.processor.data | |
| self.assertIn('Parameters', data.columns) | |
| self.assertIn('MMLU_average', data.columns) | |
| # check number of columns | |
| self.assertEqual(len(data.columns), 63) | |
| # check that the number of rows is correct | |
| def test_rows(self): | |
| data = self.processor.data | |
| self.assertEqual(len(data), 992) | |
| # check that mc1 column exists | |
| def test_mc1(self): | |
| data = self.processor.data | |
| self.assertIn('harness|truthfulqa:mc1', data.columns) | |
| # test that a column that contains truthfulqa:mc does not exist | |
| def test_truthfulqa_mc(self): | |
| data = self.processor.data | |
| self.assertNotIn('truthfulqa:mc', data.columns) | |
| if __name__ == '__main__': | |
| unittest.main() |