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sim.py
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sim.py
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from matplotlib import pyplot as plt
import numpy as np
from components import *
from utils import *
start = 0
end = 1000
steps = 100000
dt = (end - start) / steps
vco = VCO(0.3, 0.05)
phase_detector = PhaseDetector()
low_pass = LowPass(0.001)
noise_f = sine_wave_f(0.01, 0.1, 0)
nrz = NRZ_TX(0.295, noise_f, [0, 0, 1] * 1000)
edge_detector = EdgeDetector(0.3)
bbd = BangBangPD()
v_n_s = []
v_o_s = []
v_bb_s = []
v_d_s = []
v_f_s = []
v_e_s = []
ts = np.linspace(start, end, steps)
last_v_f = 0
for t in ts:
nrz.step(t, dt)
v_n = nrz.out()
edge_detector.step(t, dt, v_n)
v_e = edge_detector.out()
vco.step(t, dt, last_v_f)
v_o = vco.out()
phase_detector.step(t, dt, v_e, v_o)
v_d = phase_detector.out()
bbd.step(t, dt, v_n, v_o)
v_bb = bbd.out()
low_pass.step(t, dt, v_bb)
v_f = low_pass.out()
v_n_s.append(v_n)
v_o_s.append(v_o)
v_d_s.append(v_d)
v_f_s.append(v_f)
v_e_s.append(v_e)
v_bb_s.append(v_bb)
last_v_f = v_f
def graph():
slc = slice(0, 100000)
fig, axs = plt.subplots(3, sharex=True)
axs[0].plot(ts[slc], v_n_s[slc], color='r', label='nrz')
axs[0].plot(ts[slc], v_o_s[slc], color='g', label='output')
#axs[1].plot(ts[slc], v_e_s[slc], color='black', label='edge')
axs[1].plot(ts[slc], v_o_s[slc], color='g', label='output')
axs[2].plot(ts[slc], v_bb_s[slc], color='b', label='detector')
axs[2].plot(ts[slc], v_f_s[slc], color='y', label='filtered')
fig.legend()
plt.show()
graph()