import unittest
import numpy as np
import brainbox.task.passive as passive
from iblutil.numerical import ismember2d
[docs]class TestPassive(unittest.TestCase):
[docs] def test_rf_map(self):
"""
"""
# Simulate fake rfmap data
test_frames = np.full((60, 15, 15), 128, dtype='uint8')
# Test on and off individually
test_frames[10:20, 8, 8] = 0
test_frames[25:35, 10, 13] = 255
# Test that interleaved are detected correctly
test_frames[40:50, 4, 9] = 0
test_frames[42:52, 6, 10] = 255
test_frames[42:55, 11, 4] = 0
test_frames[50:60, 8, 8] = 0
test_times = np.arange(60)
rf_map = {}
rf_map['times'] = test_times
rf_map['frames'] = test_frames
rf_map_times, rf_map_pos, rf_stim_frames = passive.get_on_off_times_and_positions(rf_map)
assert(all(rf_map_times == test_times))
assert(rf_map_pos.shape == (15 * 15, 2))
assert(len(rf_stim_frames['on']) == 15 * 15)
assert(len(rf_stim_frames['off']) == 15 * 15)
# Off is for the 0 ones
assert(all(rf_stim_frames['off'][ismember2d(rf_map_pos, np.array([[8, 8]]))[0]][0][0]
== [10, 50]))
assert(rf_stim_frames['off'][ismember2d(rf_map_pos, np.array([[4, 9]]))[0]][0][0] == 40)
assert(rf_stim_frames['off'][ismember2d(rf_map_pos, np.array([[11, 4]]))[0]][0][0] == 42)
# On is for the 255 ones
assert(rf_stim_frames['on'][ismember2d(rf_map_pos, np.array([[10, 13]]))[0]][0][0] == 25)
assert(rf_stim_frames['on'][ismember2d(rf_map_pos, np.array([[6, 10]]))[0]][0][0] == 42)
# Next test that the firing rate function works
# Basically just make one square responsive
spike_times = np.arange(25, 35, 0.01)
spike_depths = 500 * np.ones_like(spike_times)
rf_map_avg, depths = passive.get_rf_map_over_depth(rf_map_times, rf_map_pos,
rf_stim_frames, spike_times,
spike_depths, x_lim=[0, 60])
non_zero = np.where(rf_map_avg['on'] != 0)
assert(np.argmin(np.abs(depths - 500)) == non_zero[0][0])
assert(all(non_zero[1] == 10))
assert (all(non_zero[2] == 13))
assert(np.all(rf_map_avg['off'] == 0))
rf_svd = passive.get_svd_map(rf_map_avg)
# Make sure that the one responsive element is non-zero
assert(rf_svd['on'][non_zero[0][0]][non_zero[1][0], non_zero[2][0]] != 0)
# But that all the rest are zero
rf_svd['on'][non_zero[0][0]][non_zero[1][0], non_zero[2][0]] = 0
assert(np.all(np.isclose(np.vstack(rf_svd['on']), 0)))
assert(np.all(np.vstack(rf_svd['off']) == 0))
[docs] def test_stim_aligned(self):
# Make random times
aud_stim = {}
aud_stim['valveOn'] = np.array([10, 20, 30])
spike_times = np.r_[np.arange(8, 9.6, 0.01), np.arange(9.6, 15, 0.002),
np.arange(18, 19.6, 0.005), np.arange(19.6, 25, 0.002),
np.arange(28, 29.6, 0.01), np.arange(29.6, 35, 0.002)]
spike_depths = np.zeros_like(spike_times)
stim_activity = passive.get_stim_aligned_activity(aud_stim, spike_times, spike_depths,
z_score_flag=False, x_lim=[0, 40])
assert(list(stim_activity.keys()) == ['valveOn'])
# The first may be a bit different due to overlap with noise floor
assert(all(stim_activity['valveOn'][0][1:] == 5))
# make sure the rest of the depths are all zero
assert(np.all(stim_activity['valveOn'][1:] == 0))