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
// 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)
plt.ylim(0, 1.2)
