def test_dmos_subjective_model_dscore_mode_same(self):
subjective_model = DmosModel.from_dataset_file(self.dataset_filepath)
result = subjective_model.run_modeling(normalize_final=True)
scores = result['quality_scores']
self.assertAlmostEquals(scores[0], 1.0440613892053001, places=4)
self.assertAlmostEquals(scores[10], -1.3452648137895296, places=4)
self.assertAlmostEquals(np.mean(scores), 0.0, places=4)
def test_dmos_subjective_model_dscore_mode_same(self):
subjective_model = DmosModel.from_dataset_file(self.dataset_filepath)
result = subjective_model.run_modeling(normalize_final=True)
scores = result['quality_scores']
self.assertAlmostEquals(scores[0], 1.0440613892053001, places=4)
self.assertAlmostEquals(scores[10], -1.3452648137895296, places=4)
self.assertAlmostEquals(np.mean(scores), 0.0, places=4)
def test_dmos_subjective_model(self):
subjective_model = DmosModel.from_dataset_file(self.dataset_filepath)
result = subjective_model.run_modeling()
scores = result['quality_scores']
self.assertAlmostEquals(scores[0], 5.0, places=4)
self.assertAlmostEquals(scores[10], 2.1923076923076921, places=4)
self.assertAlmostEquals(np.mean(scores), 3.7731256085686473, places=4)
def test_dmos_subjective_model(self):
subjective_model = DmosModel.from_dataset_file(self.dataset_filepath)
result = subjective_model.run_modeling()
scores = result['quality_scores']
self.assertAlmostEquals(scores[0], 5.0, places=4)
self.assertAlmostEquals(scores[10], 2.1923076923076921, places=4)
self.assertAlmostEquals(np.mean(scores), 3.7731256085686473, places=4)