def test_convert_to_long(): audio_dir = join(get_test_data_path(), 'audio') stim = AudioStim(join(audio_dir, 'barber.wav')) ext = STFTAudioExtractor(frame_size=1., spectrogram=False, freq_bins=[(100, 300), (300, 3000), (3000, 20000)]) timeline = ext.transform(stim) long_timeline = to_long_format(timeline) assert long_timeline.shape == (timeline.to_df().shape[0] * 3, 4) assert 'feature' in long_timeline.columns assert 'value' in long_timeline.columns assert '100_300' not in long_timeline.columns timeline = ExtractorResult.merge_features([timeline]) long_timeline = to_long_format(timeline) assert 'feature' in long_timeline.columns assert 'extractor' in long_timeline.columns assert '100_300' not in long_timeline.columns
def test_convert_to_long_graph(): image_dir = join(get_test_data_path(), 'image') stim = ImageStim(join(image_dir, 'obama.jpg')) ext = GoogleVisionAPIFaceExtractor() g = Graph([ext]) timeline = g.run(stim) long_timeline = to_long_format(timeline) assert 'feature' in long_timeline.columns assert 'extractor' in long_timeline.columns assert 'history' in long_timeline.columns