def test_init(self):
ts = TimeSeries('test_ts', list(), 'unit', timestamps=list())
iS = IndexSeries('test_iS', list(), 'unit', ts, timestamps=list())
self.assertEqual(iS.name, 'test_iS')
self.assertEqual(iS.unit, 'unit')
self.assertEqual(iS.indexed_timeseries, ts)
def test_show_index_series():
data = np.array([12, 14, 16, 18, 20, 22, 24, 26])
indexed_timeseries = TimeSeries(name='Index Series time data',
data=np.random.rand(800).reshape((8, 10, 10)), rate=1.)
index_series = IndexSeries(name='Sample Index Series', data=data,
indexed_timeseries=indexed_timeseries, rate=1.)
assert isinstance(show_index_series(index_series, default_neurodata_vis_spec), widgets.Widget)
def add_stimulus_index(nwbfile, stimulus_index, nwb_template):
image_index = IndexSeries(name=nwb_template.name,
data=stimulus_index['image_index'].values,
unit='None',
indexed_timeseries=nwb_template,
timestamps=stimulus_index['start_time'].values)
nwbfile.add_stimulus(image_index)
def test_init(self):
ts = TimeSeries(name='test_ts',
data=[1, 2, 3],
unit='unit',
timestamps=[0.1, 0.2, 0.3])
iS = IndexSeries(name='test_iS',
data=[1, 2, 3],
unit='N/A',
indexed_timeseries=ts,
timestamps=[0.1, 0.2, 0.3])
self.assertEqual(iS.name, 'test_iS')
self.assertEqual(iS.unit, 'N/A')
self.assertIs(iS.indexed_timeseries, ts)
########################################
# 2) Next, we add stimuli templates (one for each type of stimulus), and a data series that indexes these templates to
# describe what stimulus was being shown during the experiment.
for stimulus in stimulus_list:
visual_stimulus_images = ImageSeries(
name=stimulus,
source='NA',
data=dataset.get_stimulus_template(stimulus),
unit='NA',
format='raw',
timestamps=[0.0])
image_index = IndexSeries(
name=stimulus,
source='NA',
data=dataset.get_stimulus_table(stimulus).frame.values,
unit='NA',
indexed_timeseries=visual_stimulus_images,
timestamps=timestamps[dataset.get_stimulus_table(
stimulus).start.values])
nwbfile.add_stimulus_template(visual_stimulus_images)
nwbfile.add_stimulus(image_index)
########################################
# 3) Besides the two-photon calcium image stack, the running speed of the animal was also recordered in this experiment.
# We can store this data as a TimeSeries, in the acquisition portion of the file.
running_speed = TimeSeries(name='running_speed',
source='Allen Brain Observatory: Visual Coding',
data=running_data,
timestamps=timestamps,
unit='cm/s')