def test_z_filter(self): source = join(TEST_FILE_PATH, u'pauksciai.csv') output = join(TEST_FILE_PATH, 'tmp', u'pauksciai_z_filter.csv') attr = 2 filter(source, output, attr, filter='outliers', update_value=True) self.assertTrue(exists(output)) with open(output) as output_file: for attr_list in csv.reader(output_file): # Assert only strutis yra self.assertTrue(fabs(float(attr_list[attr])) > 3)
def test_quartile_filter(self): # Selected attr is normalised using quartile transformation and filtered source = join(TEST_FILE_PATH, u'pauksciai.csv') output = join(TEST_FILE_PATH, 'tmp', u'pauksciai_quartil_filter.csv') attr = 2 filter(source, output, attr, filter='outliers', method='quartil') self.assertTrue(exists(output)) with open(output) as output_file: for attr_list in csv.reader(output_file): self.assertTrue('strutis' in attr_list[1])