def test_nonlinear(self):
sm = SimModel()
f = lambda x: x
nl1 = Direct(1, 1, f)
nl2 = Direct(2, 2, f)
sm.nonlinearity(nl1)
self.assertEqual(len(sm.nonlinearities), 1)
sm.nonlinearity(nl1)
self.assertEqual(len(sm.nonlinearities), 1) # Already in there
sm.nonlinearity(nl2)
self.assertEqual(len(sm.nonlinearities), 2)
sm.nonlinearity(Direct(1, 1, f)) # Same params as nl1, but different
self.assertEqual(len(sm.nonlinearities), 3)
def test_simple_direct_mode():
m = SimModel()
one, steps, simtime = setup_simtime(m)
sig = m.signal()
pop = m.nonlinearity(Direct(n_in=1, n_out=1, fn=np.sin))
m.encoder(simtime, pop, weights=[[1.0]])
m.decoder(pop, sig, weights=[[1.0]])
m.transform(1.0, sig, sig)
sim = Simulator(m)
for i in range(5):
sim.step()
if i:
assert sim.signals[sig] == np.sin(sim.signals[simtime] - 0.001)
