def test_bin_shuffling_output_format(self):
self.bin_size = 3 * pq.ms
self.max_displacement = 10
spiketrain = neo.SpikeTrain([90, 93, 97, 100, 105, 150, 180, 350] *
pq.ms,
t_stop=.5 * pq.s)
binned_spiketrain = conv.BinnedSpikeTrain(spiketrain, self.bin_size)
n_surrogates = 2
for sliding in (True, False):
surrogate_trains = surr.bin_shuffling(
binned_spiketrain,
max_displacement=self.max_displacement,
n_surrogates=n_surrogates,
sliding=sliding)
self.assertIsInstance(surrogate_trains, list)
self.assertEqual(len(surrogate_trains), n_surrogates)
self.assertIsInstance(surrogate_trains[0], conv.BinnedSpikeTrain)
for surrogate_train in surrogate_trains:
self.assertEqual(surrogate_train.t_start,
binned_spiketrain.t_start)
self.assertEqual(surrogate_train.t_stop,
binned_spiketrain.t_stop)
self.assertEqual(surrogate_train.n_bins,
binned_spiketrain.n_bins)
self.assertEqual(surrogate_train.bin_size,
binned_spiketrain.bin_size)
def test_bin_shuffling_empty_train(self):
self.bin_size = 3 * pq.ms
self.max_displacement = 10
empty_spiketrain = neo.SpikeTrain([] * pq.ms, t_stop=500 * pq.ms)
binned_spiketrain = conv.BinnedSpikeTrain(empty_spiketrain,
self.bin_size)
surrogate_train = surr.bin_shuffling(
binned_spiketrain, max_displacement=self.max_displacement,
n_surrogates=1)[0]
self.assertEqual(np.sum(surrogate_train.to_bool_array()), 0)