diff --git a/tests/test_augmentor.py b/tests/test_augmentor.py index 76fd321a..17491704 100755 --- a/tests/test_augmentor.py +++ b/tests/test_augmentor.py @@ -11,49 +11,53 @@ import numpy as np random_seed=0 #audio instance -audio_data=[3.05175781e-05, -8.54492188e-04, -1.09863281e-03, -9.46044922e-04,\ - -1.31225586e-03, -1.09863281e-03, -1.73950195e-03, -2.10571289e-03,\ - -2.04467773e-03, -1.46484375e-03, -1.43432617e-03, -9.46044922e-04,\ - -1.95312500e-03, -1.86157227e-03, -2.10571289e-03, -2.31933594e-03,\ - -2.01416016e-03, -2.62451172e-03, -2.07519531e-03, -2.38037109e-03] +audio_data = [3.0517571e-05, -8.54492188e-04, -1.09863281e-03, -9.4604492e-04,\ + -1.31225586e-03, -1.09863281e-03, -1.73950195e-03, -2.1057189e-03,\ + -2.04467773e-03, -1.46484375e-03, -1.43432617e-03, -9.4604492e-04,\ + -1.95312500e-03, -1.86157227e-03, -2.10571289e-03, -2.3193354e-03,\ + -2.01416016e-03, -2.62451172e-03, -2.07519531e-03, -2.3803719e-03] audio_data = np.array(audio_data) samplerate = 10 class TestAugmentor(unittest.TestCase): def test_volume(self): - augmentation_config='[{"type": "volume","params": {"min_gain_dBFS": -15, "max_gain_dBFS": 15},"prob": 1.0}]' - augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config, - random_seed=random_seed) - audio_segment = audio.AudioSegment(audio_data, samplerate) - augmentation_pipeline.transform_audio(audio_segment) - original_audio = audio.AudioSegment(audio_data, samplerate) - self.assertFalse(np.any(audio_segment.samples == original_audio.samples)) + config_json = '[{"type": "volume","params": {"min_gain_dBFS": -15, '\ + '"max_gain_dBFS": 15},"prob": 1.0}]' + aug_pipeline = AugmentationPipeline(augmentation_config=config_json, + random_seed=random_seed) + audio_seg = audio.AudioSegment(audio_data, samplerate) + aug_pipeline.transform_audio(audio_seg) + orig_audio = audio.AudioSegment(audio_data, samplerate) + self.assertFalse(np.any(audio_seg.samples == orig_audio.samples)) def test_speed(self): - augmentation_config='[{"type": "speed","params": {"min_speed_rate": 1.2,"max_speed_rate": 1.4},"prob": 1.0}]' - augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config, - random_seed=random_seed) - audio_segment = audio.AudioSegment(audio_data, samplerate) - augmentation_pipeline.transform_audio(audio_segment) - original_audio = audio.AudioSegment(audio_data, samplerate) - self.assertFalse(np.any(audio_segment.samples == original_audio.samples)) + config_json = '[{"type":"speed","params": {"min_speed_rate": 1.2,' \ + '"max_speed_rate": 1.4},"prob": 1.0}]' + aug_pipeline = AugmentationPipeline(augmentation_config=config_json, + random_seed=random_seed) + audio_seg = audio.AudioSegment(audio_data, samplerate) + aug_pipeline.transform_audio(audio_seg) + orig_audio = audio.AudioSegment(audio_data, samplerate) + self.assertFalse(np.any(audio_seg.samples == orig_audio.samples)) def test_resample(self): - augmentation_config='[{"type": "resample","params": {"new_sample_rate":5},"prob": 1.0}]' - augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config, - random_seed=random_seed) - audio_segment = audio.AudioSegment(audio_data, samplerate) - augmentation_pipeline.transform_audio(audio_segment) - self.assertTrue(audio_segment.sample_rate == 5) + config_json = '[{"type":"resample","params": {"new_sample_rate":5},'\ + '"prob": 1.0}]' + aug_pipeline = AugmentationPipeline(augmentation_config=config_json, + random_seed=random_seed) + audio_seg = audio.AudioSegment(audio_data, samplerate) + aug_pipeline.transform_audio(audio_seg) + self.assertTrue(audio_seg.sample_rate == 5) def test_bayesial(self): - augmentation_config='[{"type": "bayesian_normal","params": {"target_db": -20, "prior_db": -4, "prior_samples": -8, "startup_delay": 0.0},"prob": 1.0}]' - augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config, - random_seed=random_seed) - audio_segment = audio.AudioSegment(audio_data, samplerate) - augmentation_pipeline.transform_audio(audio_segment) - original_audio = audio.AudioSegment(audio_data, samplerate) - self.assertFalse(np.any(audio_segment.samples == original_audio.samples)) + config_json = '[{"type":"bayesian_normal","params":{"target_db":-20,' \ + '"prior_db":-4, "prior_samples": -8, "startup_delay": 0.0},"prob":1.0}]' + aug_pipeline = AugmentationPipeline(augmentation_config=config_json, + random_seed=random_seed) + audio_seg = audio.AudioSegment(audio_data, samplerate) + aug_pipeline.transform_audio(audio_seg) + orig_audio = audio.AudioSegment(audio_data, samplerate) + self.assertFalse(np.any(audio_seg.samples == orig_audio.samples)) if __name__ == '__main__': unittest.main()