def test_mapping(Simulator, plt, seed):
sys = Alpha(0.1)
syn = Lowpass(0.01)
gsyn = 2*syn # scaled lowpass
isyn = 2/s # scaled integrator
dt = 0.001
ss = ss2sim(sys, syn, None) # normal lowpass, continuous
dss = ss2sim(sys, syn, dt) # normal lowpass, discrete
gss = ss2sim(sys, gsyn, None) # scaled lowpass, continuous
gdss = ss2sim(sys, gsyn, dt) # scaled lowpass, discrete
iss = ss2sim(sys, isyn, None) # scaled integrator, continuous
idss = ss2sim(sys, isyn, dt) # scaled integrator, discrete
assert ss.analog and gss.analog and iss.analog
assert not (dss.analog or gdss.analog or idss.analog)
with Network(seed=seed) as model:
stim = nengo.Node(output=lambda t: np.sin(20*np.pi*t))
probes = []
for mapped, synapse in ((ss, syn), (dss, syn), (gss, gsyn),
(gdss, gsyn), (iss, isyn), (idss, isyn)):
A, B, C, D = mapped.ss
x = nengo.Node(size_in=2)
y = nengo.Node(size_in=1)
nengo.Connection(stim, x, transform=B, synapse=synapse)
nengo.Connection(x, x, transform=A, synapse=synapse)
nengo.Connection(x, y, transform=C, synapse=None)
nengo.Connection(stim, y, transform=D, synapse=None)
probes.append(nengo.Probe(y))
p_stim = nengo.Probe(stim)
pss, pdss, pgss, pgdss, piss, pidss = probes
with Simulator(model, dt=dt) as sim:
sim.run(1.0)
expected = shift(sys.filt(sim.data[p_stim], dt))
plt.plot(sim.trange(), sim.data[pss], label="Continuous", alpha=0.5)
plt.plot(sim.trange(), sim.data[pdss], label="Discrete", alpha=0.5)
plt.plot(sim.trange(), sim.data[pgss], label="Gain Cont.", alpha=0.5)
plt.plot(sim.trange(), sim.data[pgdss], label="Gain Disc.", alpha=0.5)
plt.plot(sim.trange(), sim.data[piss], label="Integ Cont.", alpha=0.5)
plt.plot(sim.trange(), sim.data[pidss], label="Integ Disc.", alpha=0.5)
plt.plot(sim.trange(), expected, label="Expected", linestyle='--')
plt.legend()
assert np.allclose(sim.data[pss], expected, atol=0.01)
assert np.allclose(sim.data[pdss], expected)
assert np.allclose(sim.data[pgss], expected, atol=0.01)
assert np.allclose(sim.data[pgdss], expected)
assert np.allclose(sim.data[piss], expected, atol=0.01)
assert np.allclose(sim.data[pidss], expected)
def test_balred(rng):
dt = 0.001
sys = Alpha(0.01) + Lowpass(0.001)
u = rng.normal(size=2000)
expected = sys.filt(u, dt)
def check(order, within, tol, method='del'):
redsys = balred(sys, order, method=method)
assert redsys.order_den <= order
actual = redsys.filt(u, dt)
assert abs(rmse(expected, actual) - within) < tol
with warns(UserWarning):
check(4, 0, 1e-13)
with warns(UserWarning):
check(3, 0, 1e-13)
check(2, 0.03, 0.01)
check(1, 0.3, 0.1)