def eye():
"""
Adds eye Position and PupilTracking to behavior processing module.
Needs data from eye.timestamps.npy, eye.area.npy, and eye.xyPos.npy.
"""
eye_timestamps = read_npy_file('eye.timestamps.npy')[:,
1] # takes out index
eye_area = read_npy_file('eye.area.npy')
eye_xy_pos = read_npy_file('eye.xyPos.npy')
pupil = TimeSeries(
name='eye_area',
timestamps=eye_timestamps,
data=np.ravel(eye_area),
unit='arb. unit',
description='Features extracted from the video of the right eye.',
comments='The area of the pupil extracted with DeepLabCut. Note that '
'it is relatively very small during the discrimination task '
'and during the passive replay because the three screens are '
'medium-grey at this time and black elsewhere - so the much '
'brighter overall luminance levels lead to relatively '
'constricted pupils.')
eye_xy = TimeSeries(
name='eye_xy_positions',
timestamps=eye_timestamps,
data=eye_xy_pos, # currently as [x, y] pairs
unit='arb. unit',
description='Features extracted from the video of the right eye.',
comments='The 2D position of the center of the pupil in the video '
'frame. This is not registered to degrees visual angle, but '
'could be used to detect saccades or other changes in eye position.')
pupil_track = PupilTracking(pupil)
pupil_track.add_timeseries(eye_xy)
behavior_module.add_data_interface(pupil_track)
def test_init(self):
ts = TimeSeries('test_ts',
np.ones((2, 2)),
'unit',
timestamps=[1., 2., 3.])
pt = PupilTracking(ts)
self.assertEqual(pt.time_series['test_ts'], ts)
def test_init(self):
ts = TimeSeries('test_ts',
'a hypothetical source',
list(),
'unit',
timestamps=list())
pt = PupilTracking('test_pt', ts)
self.assertEqual(pt.source, 'test_pt')
self.assertEqual(pt.time_series, ts)
def test_init(self):
ts = TimeSeries('test_ts', list(), 'unit', timestamps=list())
pt = PupilTracking(ts)
self.assertEqual(pt.time_series['test_ts'], ts)