mirror of
https://github.com/romanz/amodem.git
synced 2026-02-07 01:18:02 +08:00
67 lines
1.7 KiB
Python
67 lines
1.7 KiB
Python
from amodem import train, dsp, config, send
|
|
from numpy.linalg import norm
|
|
import numpy as np
|
|
import itertools
|
|
|
|
def test_fir():
|
|
a = [1, 0.8, -0.1, 0, 0]
|
|
tx = train.equalizer
|
|
rx = dsp.lfilter(x=tx, b=[1], a=a)
|
|
h_ = dsp.estimate(x=rx, y=tx, order=len(a))
|
|
tx_ = dsp.lfilter(x=rx, b=h_, a=[1])
|
|
assert norm(h_ - a) < 1e-12
|
|
assert (norm(tx - tx_) / norm(tx)) < 1e-12
|
|
|
|
|
|
def test_iir():
|
|
alpha = 0.1
|
|
b = [1, -alpha]
|
|
tx = train.equalizer
|
|
rx = dsp.lfilter(x=tx, b=b, a=[1])
|
|
h_ = dsp.estimate(x=rx, y=tx, order=20)
|
|
tx_ = dsp.lfilter(x=rx, b=h_, a=[1])
|
|
|
|
h_expected = np.array([alpha ** i for i in range(len(h_))])
|
|
assert norm(h_ - h_expected) < 1e-12
|
|
assert (norm(tx - tx_) / norm(tx)) < 1e-12
|
|
|
|
|
|
import random
|
|
|
|
_constellation = [1, 1j, -1, -1j]
|
|
|
|
def train_symbols(length, seed=0):
|
|
r = random.Random(seed)
|
|
choose = lambda: [r.choice(_constellation) for j in range(config.Nfreq)]
|
|
return np.array([choose() for i in range(length)])
|
|
|
|
def modulator(length):
|
|
symbols = train_symbols(length)
|
|
carriers = send.sym.carrier
|
|
result = []
|
|
for s in symbols:
|
|
result.append(np.dot(s, carriers) / len(carriers))
|
|
result = np.concatenate(result).real
|
|
assert np.max(np.abs(result)) <= 1
|
|
return result
|
|
|
|
def demodulator(signal):
|
|
signal = itertools.chain(signal, itertools.repeat(0))
|
|
return dsp.Demux(signal, config.frequencies)
|
|
|
|
def test_training():
|
|
L = 1000
|
|
t1 = train_symbols(L)
|
|
t2 = train_symbols(L)
|
|
assert (t1 == t2).all()
|
|
|
|
def test_modem():
|
|
L = 1000
|
|
x = modulator(L)
|
|
s = demodulator(x)
|
|
s = list(itertools.islice(s, L))
|
|
sent = train_symbols(L)
|
|
received = np.array(s) * len(send.sym.carrier)
|
|
err = sent - received
|
|
assert norm(err) < 1e-12
|