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