def setUp(self): dataset_filepath = config.ROOT + '/python/test/resource/NFLX_dataset_public_raw.py' dataset = import_python_file(dataset_filepath) np.random.seed(0) info_dict = { 'corrupt_probability': 0.1, } self.dataset_reader = CorruptDataRawDatasetReader(dataset, input_dict=info_dict)
class CorruptDataDatasetReaderTest(unittest.TestCase): def setUp(self): dataset_filepath = config.ROOT + '/python/test/resource/NFLX_dataset_public_raw.py' dataset = import_python_file(dataset_filepath) np.random.seed(0) info_dict = { 'corrupt_probability': 0.1, } self.dataset_reader = CorruptDataRawDatasetReader(dataset, input_dict=info_dict) def test_opinion_score_2darray(self): os_2darray = self.dataset_reader.opinion_score_2darray self.assertAlmostEquals(np.mean(np.std(os_2darray, axis=1)), 0.79796204942957094, places=4) def test_to_dataset(self): dataset = self.dataset_reader.to_dataset() old_scores = [ dis_video['os'] for dis_video in self.dataset_reader.dataset.dis_videos ] new_scores = [dis_video['os'] for dis_video in dataset.dis_videos] self.assertNotEquals(old_scores, new_scores)
def run_one_corrput_prob(corrupt_prob, dataset, seed): np.random.seed(seed) info_dict = { 'corrupt_probability': corrupt_prob, } dataset_reader = CorruptDataRawDatasetReader(dataset, input_dict=info_dict) subjective_model = model_class(dataset_reader) try: result = subjective_model.run_modeling(normalize_final=False) except ValueError as e: print 'Warning: {}, return result None'.format(e) result = None return dataset_reader, result
class CorruptDataDatasetReaderTest(unittest.TestCase): def setUp(self): dataset_filepath = config.ROOT + '/python/test/resource/NFLX_dataset_public_raw.py' dataset = import_python_file(dataset_filepath) np.random.seed(0) info_dict = { 'corrupt_probability': 0.1, } self.dataset_reader = CorruptDataRawDatasetReader(dataset, input_dict=info_dict) def test_opinion_score_2darray(self): os_2darray = self.dataset_reader.opinion_score_2darray self.assertAlmostEquals(np.mean(np.std(os_2darray, axis=1)), 0.79796204942957094, places=4) def test_to_dataset(self): dataset = self.dataset_reader.to_dataset() old_scores = [dis_video['os'] for dis_video in self.dataset_reader.dataset.dis_videos] new_scores = [dis_video['os'] for dis_video in dataset.dis_videos] self.assertNotEquals(old_scores, new_scores)