def test_alpha(Simulator, plt):
dt = 1e-3
tau = 0.03
b, a = [0.00054336, 0.00053142], [1, -1.9344322, 0.93550699]
# ^^^ these coefficients found for tau=0.03 and dt=1e-3
# scipy.signal.cont2discrete(([1], [tau**2, 2*tau, 1]), dt)
# b = [0.00054336283526056767, 0.00053142123234546667]
# a = [1, -1.9344322009640118, 0.93550698503161778]
# ^^^ these coefficients found by the exact algorithm used in Builder
t, x, yhat = run_synapse(Simulator, nengo.synapses.Alpha(tau), dt=dt)
y = lti(x, (b, a))
assert allclose(t, y, yhat, delay=dt, atol=5e-6, plt=plt)
def test_lti_lowpass():
dt = 1e-3
tend = 3.
t = dt * np.arange(tend / dt)
nt = len(t)
tau = 1e-2
d = -np.expm1(-dt / tau)
a = [d]
b = [1, d - 1]
u = np.random.normal(size=(nt, 10))
x = filt(u, tau / dt)
y = lti(u, (a, b))
assert np.allclose(x, y)
def test_general(Simulator, plt):
import scipy.signal
dt = 1e-3
order = 4
tau = 0.03
num, den = scipy.signal.butter(order, 1. / tau, analog=True)
num, den = num.real, den.real
numi, deni, dt = scipy.signal.cont2discrete((num, den), dt)
t, x, yhat = run_synapse(
Simulator, nengo.synapses.LinearFilter(num, den), dt=dt)
y = lti(x, (numi, deni))
assert allclose(t, y, yhat, plt=plt)
def test_general(Simulator):
import scipy.signal
dt = 1e-3
order = 4
tau = 0.03
num, den = scipy.signal.butter(order, 1. / tau, analog=True)
num, den = num.real, den.real
numi, deni, dt = scipy.signal.cont2discrete((num, den), dt)
t, x, yhat = run_synapse(Simulator,
nengo.synapses.LinearFilter(num, den),
dt=dt)
y = lti(x, (numi, deni))
assert allclose(t,
y.flatten(),
yhat.flatten(),
plotter=Plotter(Simulator),
filename='test_synapse.test_general.pdf')
def test_alpha(Simulator):
dt = 1e-3
tau = 0.03
b, a = [0.00054336, 0.00053142], [1, -1.9344322, 0.93550699]
# ^^^ these coefficients found for tau=0.03 and dt=1e-3
# scipy.signal.cont2discrete(([1], [tau**2, 2*tau, 1]), dt)
# b = [0.00054336283526056767, 0.00053142123234546667]
# a = [1, -1.9344322009640118, 0.93550698503161778]
# ^^^ these coefficients found by the exact algorithm used in Builder
t, x, yhat = run_synapse(Simulator, nengo.synapses.Alpha(tau), dt=dt)
y = lti(x, (b, a))
assert allclose(t,
y.flatten(),
yhat.flatten(),
delay=1,
atol=5e-6,
plotter=Plotter(Simulator),
filename='test_synapse.test_alpha.pdf')
