def test_cubic_interpolation_warning(self):
pytest.importorskip("scipy")
# cubic interpolation with 0 not in times
process = Piecewise({0.001: 0, 0.1: 0.1}, interpolation="cubic")
with pytest.warns(UserWarning,
match="'cubic' interpolation.*for t=0.0"):
try:
process.run(0.001)
except ValueError:
pass # scipy may raise a ValueError
def product(x):
return x[0] * x[1]
nengo.Connection(combined, prod, function=product)
with model:
inputA_probe = nengo.Probe(input_A)
inputB_probe = nengo.Probe(input_B)
A_probe = nengo.Probe(A, synapse=0.01)
B_probe = nengo.Probe(B, synapse=0.01)
combined_probe = nengo.Probe(combined, synapse=0.01)
prod_probe = nengo.Probe(prod, synapse=0.01)
with nengo.Simulator(model) as sim:
sim.run(5)
plt.figure()
plt.plot(sim.trange(), sim.data[A_probe], label="Decoded A")
plt.plot(sim.trange(), sim.data[B_probe], label="Decoded B")
plt.plot(sim.trange(), sim.data[prod_probe], label="Decoded product")
plt.plot(sim.trange(),
correct_ans.run(sim.time, dt=sim.dt),
c="k",
label="Actual product")
plt.legend(loc="best")
plt.show()
nengo.Connection(control, A[1], synapse=0.005)
with model:
nengo.Connection(A,
A[0],
function=lambda x: x[0] * x[1] + x[0],
synapse=tau)
A_probe = nengo.Probe(A, "decoded_output", synapse=0.01)
with nengo.Simulator(model) as sim:
sim.run(1.4)
t = sim.trange()
dt = t[1] - t[0]
input_sig = input_func.run(t[-1], dt=dt)
control_sig = control_func.run(t[-1], dt=dt)
ref = dt * np.cumsum(input_sig)
plt.figure(figsize=(6, 8))
plt.subplot(211)
plt.plot(t, input_sig, label="input")
plt.ylabel("label")
plt.legend()
plt.subplot(212)
plt.plot(t, ref, "k--", label="exact")
plt.plot(t, sim.data[A_probe][:, 0], label="A (value)")
plt.plot(t, sim.data[A_probe][:, 1], label="A (control)")
plt.ylabel("x(t)")
plt.legend()
