def test_noise(step_size=0.00005, tlen=1.00, max_freq=20e3):
samp_rate = 1.0 / step_size
nf = NoiseWaveform(samp_rate=samp_rate, max_freq=max_freq)
t = np.arange(0.0, tlen, step_size)
state = []
for ti in t:
s = nf.next()
state.append(s)
state = np.array(state)
play_signal(state, samp_rate)
def plot_pulse(step_size=0.00005, tlen=0.010, T0=9.0, Ee=750.0, Rg=1.0, Rk=0.40, Ra=0.05):
lf = LFWaveform(step_size)
lf.configure_params(T0, Ee, Rg, Rk, Ra)
print lf.params
t = np.arange(0.0, tlen, step_size)
state = []
for ti in t:
s = lf.next()
state.append(s)
state = np.array(state)
Ufft = np.fft.fft(state[:, 0])
Ufreq = np.fft.fftfreq(len(Ufft), d=step_size)
dUfft = np.fft.fft(state[:, 1])
dUfreq = np.fft.fftfreq(len(Ufft), d=step_size)
ftitle = '$T_0=%0.1f, E_e=%d, R_g=%0.2f, R_k=%0.2f, R_a=%0.2f, \Delta t=%0.6f$' % (T0, Ee, Rg, Rk, Ra, step_size)
twin = min(tlen, 0.075)
tsamps = int(twin / step_size)
plt.figure()
plt.subplot(2, 1, 1)
plt.plot(t[:tsamps], state[:tsamps, 0], 'g-', linewidth=2.0)
plt.axhline(color='k')
plt.axis('tight')
plt.title('$U(t)$')
plt.subplot(2, 1, 2)
plt.plot(t[:tsamps], state[:tsamps, 1], 'b-', linewidth=2.0)
plt.axhline(color='k')
plt.title('$dU(t)$')
plt.axis('tight')
plt.suptitle(ftitle)
plt.figure()
plt.subplot(2, 1, 1)
ph = (Ufreq >= 0.0) & (Ufreq <= 4000.0)
plt.plot(Ufreq[ph], np.abs(Ufft[ph]), 'g-', linewidth=2.0)
plt.title('$|U(\omega)|$')
plt.axis('tight')
plt.subplot(2, 1, 2)
ph = (Ufreq >= 0.0) & (Ufreq <= 4000.0)
plt.plot(dUfreq[ph], np.abs(dUfft[ph]), 'b-', linewidth=2.0)
plt.title('$|dU(\omega)|$')
plt.axis('tight')
plt.suptitle(ftitle)
play_signal(state[:, 1], 1.0 / step_size)