def test_transition_matrix(self):
patterns = np.array([[0, 0],
[0, 1],
[0, 1],
[1, 1],
[0, 0],
[0, 1]])
states = kl_tools.spikes2states(patterns)
desired = np.zeros((4, 4))
desired[0,1] = 2
desired[1,1] = 1
desired[1,3] = 1
desired[3,0] = 1
tr = kl_tools.transition_matrix(states, 4, dt=1)
self.assertEqual(tr.shape, (4,4))
assert_array_equal(desired, tr)
desired = np.zeros((4, 4))
desired[0,1] = 1
desired[1,3] = 1
desired[1,0] = 1
desired[3,1] = 1
tr = kl_tools.transition_matrix(states, 4, dt=2)
assert_array_equal(desired, tr)
def test_spikes2states(self):
patterns = np.array([[1, 0, 1, 0],
[1, 1, 1, 1],
[0, 0, 0, 0]])
desired = np.array([10, 15, 0])
assert_array_equal(desired,
kl_tools.spikes2states(patterns))
def test_states2distr(self):
nchannels = 4
patterns = np.array([[1, 0, 1, 0],
[1, 0, 1, 0],
[1, 0, 1, 0],
[1, 1, 1, 1],
[0, 0, 0, 0]])
states = kl_tools.spikes2states(patterns)
# histogram over all possible states
desired = np.zeros(16)
desired[10] = 3
desired[-1] = 1
desired[0] = 1
distr = kl_tools.states2distr(states, nchannels, normed=False)
self.assertEqual(len(distr), 2**nchannels)
assert_array_equal(desired, distr)
distr = kl_tools.states2distr(states, nchannels, normed=True)
self.assertEqual(len(distr), 2**nchannels)
assert_array_equal(desired/5., distr)
