def test_whitesignal_continuity(rng, plt):
"""Test that WhiteSignal is continuous over multiple periods."""
rms = 0.5
high = 10
dt = 0.001
t = 1
process = WhiteSignal(t, high=high, rms=rms)
x = process.run(4 * t, d=1, dt=dt, rng=rng)
plt.plot(process.ntrange(len(x), dt=dt), x)
# tolerances approximated from derivatives of sine wave of highest freq
safety_factor = 2.
a, f = np.sqrt(2) * rms, (2 * np.pi * high) * dt
assert abs(np.diff(x, axis=0)).max() <= safety_factor * a * f
assert abs(np.diff(x, n=2, axis=0)).max() <= safety_factor**2 * a * f**2
def test_whitesignal_continuity(rng, plt):
"""Test that WhiteSignal is continuous over multiple periods."""
rms = 0.5
high = 10
dt = 0.001
t = 1
process = WhiteSignal(t, high=high, rms=rms)
x = process.run(4 * t, d=1, dt=dt, rng=rng)
plt.plot(process.ntrange(len(x), dt=dt), x)
# tolerances approximated from derivatives of sine wave of highest freq
safety_factor = 2.
a, f = np.sqrt(2) * rms, (2 * np.pi * high) * dt
assert abs(np.diff(x, axis=0)).max() <= safety_factor * a * f
assert abs(np.diff(x, n=2, axis=0)).max() <= safety_factor**2 * a * f**2
def test_whitesignal_rms(rms, rng, plt):
d = 500
t = 1
dt = 0.001
process = WhiteSignal(t, rms=rms)
values = process.run(t, d=d, dt=dt, rng=rng)
freq, val_psd = psd(values)
trange = process.trange(t, dt=dt)
plt.subplot(2, 1, 1)
plt.title("First two D of white noise process, rms=%.1f" % rms)
plt.plot(trange, values[:, :2])
plt.xlim(right=trange[-1])
plt.subplot(2, 1, 2)
plt.title("Power spectrum")
plt.plot(freq, val_psd, drawstyle='steps')
assert np.allclose(np.std(values), rms, rtol=0.02)
assert np.allclose(val_psd[1:-1], rms, rtol=0.35)
def test_whitesignal_rms(rms, rng, plt):
d = 500
t = 1
dt = 0.001
process = WhiteSignal(t, rms=rms)
values = process.run(t, d=d, dt=dt, rng=rng)
freq, val_psd = psd(values)
trange = process.trange(t, dt=dt)
plt.subplot(2, 1, 1)
plt.title("First two D of white noise process, rms=%.1f" % rms)
plt.plot(trange, values[:, :2])
plt.xlim(right=trange[-1])
plt.subplot(2, 1, 2)
plt.title("Power spectrum")
plt.plot(freq, val_psd, drawstyle='steps')
assert np.allclose(np.std(values), rms, rtol=0.02)
assert np.allclose(val_psd[1:-1], rms, rtol=0.35)
def test_whitesignal_high(high, rng, plt):
rms = 0.5
d = 500
t = 1
dt = 0.001
process = WhiteSignal(t, high, rms=rms)
values = process.run(t, d=d, dt=dt, rng=rng)
freq, val_psd = psd(values)
trange = process.trange(t, dt=dt)
plt.subplot(2, 1, 1)
plt.title("First two D of white noise process, high=%d Hz" % high)
plt.plot(trange, values[:, :2])
plt.xlim(right=trange[-1])
plt.subplot(2, 1, 2)
plt.title("Power spectrum")
plt.plot(freq, val_psd, drawstyle='steps')
plt.xlim(right=high * 2.0)
assert np.allclose(np.std(values, axis=1), rms, rtol=0.15)
assert np.all(val_psd[npext.rfftfreq(t, dt) > high] < rms * 0.5)
def test_whitesignal_high(high, rng, plt):
rms = 0.5
d = 500
t = 1
dt = 0.001
process = WhiteSignal(t, high, rms=rms)
values = process.run(t, d=d, dt=dt, rng=rng)
freq, val_psd = psd(values)
trange = process.trange(t, dt=dt)
plt.subplot(2, 1, 1)
plt.title("First two D of white noise process, high=%d Hz" % high)
plt.plot(trange, values[:, :2])
plt.xlim(right=trange[-1])
plt.subplot(2, 1, 2)
plt.title("Power spectrum")
plt.plot(freq, val_psd, drawstyle='steps')
plt.xlim(right=high * 2.0)
assert np.allclose(np.std(values, axis=1), rms, rtol=0.15)
assert np.all(val_psd[npext.rfftfreq(t, dt) > high] < rms * 0.5)
