def test_implicit_stim_conversion():
image_dir = join(get_test_data_path(), 'image')
stim = ImageStim(join(image_dir, 'button.jpg'))
ext = LengthExtractor()
result = ext.transform(stim).to_df()
assert 'text_length' in result.columns
assert result['text_length'][0] == 4
def test_text_length_extractor():
stim = TextStim(text='hello world', onset=4.2, duration=1)
ext = LengthExtractor()
result = ext.transform(stim).to_df()
assert 'text_length' in result.columns
assert result['text_length'][0] == 11
assert result['onset'][0] == 4.2
assert result['duration'][0] == 1
def test_implicit_stim_conversion2():
audio_dir = join(get_test_data_path(), 'audio')
stim = AudioStim(join(audio_dir, 'homer.wav'))
ext = LengthExtractor()
result = ext.transform(stim)
first_word = result[0].to_df()
assert 'text_length' in first_word.columns
assert first_word['text_length'][0] > 0
def test_text_length_extractor():
stim = TextStim(text='hello world', onset=4.2, duration=1)
ext = LengthExtractor()
result = ext.transform(stim).to_df()
assert 'text_length' in result.columns
assert result['text_length'][0] == 11
assert result['onset'][0] == 4.2
assert result['duration'][0] == 1
def test_implicit_stim_conversion():
image_dir = join(get_test_data_path(), 'image')
stim = ImageStim(join(image_dir, 'button.jpg'), onset=4.2)
ext = LengthExtractor()
result = ext.transform(stim).to_df()
assert 'text_length' in result.columns
assert result['text_length'][0] == 4
assert result['onset'][0] == 4.2
def test_implicit_stim_conversion3():
video_dir = join(get_test_data_path(), 'video')
stim = VideoStim(join(video_dir, 'obama_speech.mp4'))
ext = LengthExtractor()
result = ext.transform(stim)
first_word = result[0].to_df()
# The word should be "today"
assert 'text_length' in first_word.columns
assert first_word['text_length'][0] == 5
def test_implicit_stim_conversion3():
video_dir = join(get_test_data_path(), 'video')
stim = VideoStim(join(video_dir, 'obama_speech.mp4'), onset=4.2)
ext = LengthExtractor()
result = ext.transform(stim)
first_word = result[0].to_df()
# The word should be "today"
assert 'text_length' in first_word.columns
assert first_word['text_length'][0] == 5
assert first_word['onset'][0] >= 4.2
def test_implicit_stim_conversion2():
def_conv = config.get_option('default_converters')
config.set_option('default_converters',
{'AudioStim->TextStim': ('WitTranscriptionConverter', )})
audio_dir = join(get_test_data_path(), 'audio')
stim = AudioStim(join(audio_dir, 'homer.wav'), onset=4.2)
ext = LengthExtractor()
result = ext.transform(stim)
first_word = result[0].to_df()
assert 'text_length' in first_word.columns
assert first_word['text_length'][0] > 0
assert first_word['onset'][0] >= 4.2
config.set_option('default_converters', def_conv)
def test_implicit_stim_conversion2():
def_conv = config.get_option('default_converters')
config.set_option('default_converters',
{'AudioStim->TextStim': ('WitTranscriptionConverter',)})
audio_dir = join(get_test_data_path(), 'audio')
stim = AudioStim(join(audio_dir, 'homer.wav'), onset=4.2)
ext = LengthExtractor()
result = ext.transform(stim)
first_word = result[0].to_df()
assert 'text_length' in first_word.columns
assert first_word['text_length'][0] > 0
assert first_word['onset'][0] >= 4.2
config.set_option('default_converters', def_conv)
def test_big_pipeline():
pytest.importorskip('pygraphviz')
filename = join(get_test_data_path(), 'video', 'obama_speech.mp4')
video = VideoStim(filename)
visual_nodes = [(FrameSamplingFilter(every=15), [
(TesseractConverter(), [LengthExtractor()]),
VibranceExtractor(),
'BrightnessExtractor',
])]
audio_nodes = [(VideoToAudioConverter(),
[WitTranscriptionConverter(),
'LengthExtractor'], 'video_to_audio')]
graph = Graph()
graph.add_nodes(visual_nodes)
graph.add_nodes(audio_nodes)
results = graph.run(video, merge=False)
result = merge_results(results, format='wide', extractor_names='multi')
# Test that pygraphviz outputs a file
drawfile = next(tempfile._get_candidate_names())
graph.draw(drawfile)
assert exists(drawfile)
os.remove(drawfile)
assert ('LengthExtractor', 'text_length') in result.columns
assert ('VibranceExtractor', 'vibrance') in result.columns
# assert not result[('onset', '')].isnull().any()
assert 'text[negotiations]' in result['stim_name'].values
assert 'frame[90]' in result['stim_name'].values
def test_small_pipeline():
pytest.importorskip('pytesseract')
filename = join(get_test_data_path(), 'image', 'button.jpg')
stim = ImageStim(filename)
nodes = [(TesseractConverter(), [LengthExtractor()])]
graph = Graph(nodes)
result = list(graph.run([stim], merge=False))
history = result[0].history.to_df()
assert history.shape == (2, 8)
assert history.iloc[0]['result_class'] == 'TextStim'
result = merge_results(result, format='wide', extractor_names='prepend')
assert (0, 'text[Exit]') in result['stim_name'].values
assert 'LengthExtractor#text_length' in result.columns
assert result['LengthExtractor#text_length'].values[0] == 4
def test_twitter():
# Test stim creation
pytest.importorskip('twitter')
factory = TweetStimFactory()
status_id = 821442726461931521
pliers_tweet = factory.get_status(status_id)
assert isinstance(pliers_tweet, TweetStim)
assert isinstance(pliers_tweet, CompoundStim)
assert len(pliers_tweet.elements) == 1
status_id = 884392294014746624
ut_tweet = factory.get_status(status_id)
assert len(ut_tweet.elements) == 2
# Test extraction
ext = LengthExtractor()
res = ext.transform(pliers_tweet)[0].to_df()
assert res['text_length'][0] == 104
# Test image extraction
ext = BrightnessExtractor()
res = ext.transform(ut_tweet)[0].to_df()
brightness = res['brightness'][0]
assert np.isclose(brightness, 0.54057, 1e-5)
def test_twitter():
# Test stim creation
pytest.importorskip('twitter')
factory = TweetStimFactory()
status_id = 821442726461931521
pliers_tweet = factory.get_status(status_id)
assert isinstance(pliers_tweet, TweetStim)
assert isinstance(pliers_tweet, CompoundStim)
assert len(pliers_tweet.elements) == 1
status_id = 884392294014746624
ut_tweet = factory.get_status(status_id)
assert len(ut_tweet.elements) == 2
# Test extraction
ext = LengthExtractor()
res = ext.transform(pliers_tweet)[0].to_df()
assert res['text_length'][0] == 104
# Test image extraction
ext = BrightnessExtractor()
res = ext.transform(ut_tweet)[0].to_df()
brightness = res['brightness'][0]
assert np.isclose(brightness, 0.54057, 1e-5)
def test_big_pipeline():
filename = join(get_test_data_path(), 'video', 'obama_speech.mp4')
video = VideoStim(filename)
visual_nodes = [(FrameSamplingConverter(every=15), [
(TesseractConverter(), [LengthExtractor()]),
VibranceExtractor(), 'BrightnessExtractor',
])]
audio_nodes = [(VideoToAudioConverter(), [
WitTranscriptionConverter(), 'LengthExtractor'],
'video_to_audio')]
graph = Graph()
graph.add_nodes(visual_nodes)
graph.add_nodes(audio_nodes)
result = graph.run(video)
assert ('LengthExtractor', 'text_length') in result.columns
assert ('VibranceExtractor', 'vibrance') in result.columns
# assert not result[('onset', '')].isnull().any()
assert 'text[negotiations]' in result['stim'].values
assert 'frame[90]' in result['stim'].values
def test_text_length_extractor():
stim = TextStim(text='hello world')
ext = LengthExtractor()
result = ext.transform(stim).to_df()
assert 'text_length' in result.columns
assert result['text_length'][0] == 11