def learn_step(conn):
"""Update connection matrices
Args:
conn (:class:`.Connection`): connection object
Returns:
:class:`np.ndarray`: derivative of connections (to use in
connection update rule)
ToDo:
Revise (learning needs to be updated)
"""
# TODO: test
e = conn.destination.zparams.e
zi = conn.source.z
zj_conj = np.conj(conn.destination.z) # verify which one should
# be conjugated
active = np.outer(zi*nl(zi, np.sqrt(e)),
zj_conj*nl(zj_conj, np.sqrt(e)))
return -conn.d*conn.matrix + conn.k*active
def test_nl(self):
"""Test nl(x, gamma) nonlinearity"""
self.assertEqual(utils.nl(0, 0), 1)
gamma = 0.5
self.assertEqual(utils.nl(1, gamma), 1/(1-gamma))
self.assertRaises(ZeroDivisionError, utils.nl, 1, 1)
