// lowpass filters
// ---------------------------------------------------------------------------
fig, axs = plt.subplots(2, 1)
psis_f = (psi1_f, psi2_f)
Qs = (Q, 1)
for k in range(2):
axs[k].plot(np.arange(T)/T, phi_f[0], "b")
for psi_f in psis_f[k]:
axs[k].plot(np.arange(T)/T, psi_f[0], "b")
axs[k].set_xlim(0, 0.5)
axs[k].set_ylim(0, 1.2)
axs[k].set_xlabel("\omega")
axs[k].set_ylabel("\hat\psi_j(\omega)")
axs[k].set_title("Q = {}".format(Qs[k]))
fig.suptitle(("Fourier transforms of wavelets for all scales j with the "
"corresponding lowpass filter."))
After Change
// Do the same plot for the second-order filters. Note that since here `Q = 1`,
// we obtain wavelets that have higher frequency bandwidth.
plt.figure()
plt.plot(np.arange(T)/T, phi_f[0], "r")
for psi_f in psi2_f:
plt.plot(np.arange(T)/T, psi_f[0], "b")
plt.xlim(0, 0.5)
