import commlib as cl
import numpy as np
N = 1024
TS = 1e-9
T = 20 * TS
sa2 = 1.0
t = cl.time_axis(T, N)
p = cl.square(t, TS)
f = cl.frequency_axis(t)
P = cl.spectrum(t, p)
SX = sa2 / TS * np.abs(P)**2.0
cl.plot_signal(f / 1e9, SX, close_all=True, xlabel='f [GHz]', ylabel='SX')
cl.plot_signal(f * TS,
SX / np.max(SX),
xlabel='f * TS',
ylabel='SX [normalized]',
xlim=[-1, 1],
show_grid=True)
SX1 = cl.window(f, SX, -1 / TS, +1 / TS)
total = np.trapz(SX, f)
total1 = np.trapz(SX1, f)
print('power fraction :', total1 / total)
import commlib as cl import numpy as np TS = 1e-3 # Symbol duration # symbols ak = np.array([0.5, 0.25, 1.0, 0.5]) t, x = cl.pam_waveform2(ak, TS) cl.plot_signal(t, x, plot_type='-o', close_all=True)
import commlib as cl
import matplotlib.pyplot as plt
T = 10
T1 = 1
N = 1000
t = cl.time_axis(-T, T, N)
x = cl.square(t, T1)
f = cl.frequency_axis(t)
X = cl.spectrum(t, x)
plt.close('all')
cl.plot_signal(t, x, xlabel='t', ylabel='x', figure_no=1)
cl.plot_signal(f, X, xlabel='f', ylabel='X', figure_no=2)
Et = cl.energy(t, x)
Ef = cl.energy(f, X)
print('Energy in the time domain :', Et)
print('Energy in the frequency domain :', Ef)