mirror of
https://github.com/romanz/amodem.git
synced 2026-02-06 16:48:06 +08:00
68 lines
1.6 KiB
Python
68 lines
1.6 KiB
Python
from numpy.random import RandomState
|
|
import numpy as np
|
|
|
|
import utils
|
|
from amodem import equalizer
|
|
from amodem import dsp
|
|
from amodem import config
|
|
config = config.fastest()
|
|
|
|
|
|
def assert_approx(x, y, e=1e-12):
|
|
x = x.flatten()
|
|
y = y.flatten()
|
|
assert dsp.norm(x - y) < e * dsp.norm(x)
|
|
|
|
|
|
def test_training():
|
|
L = 1000
|
|
e = equalizer.Equalizer(config)
|
|
t1 = e.train_symbols(L)
|
|
t2 = e.train_symbols(L)
|
|
assert (t1 == t2).all()
|
|
|
|
|
|
def test_commutation():
|
|
x = np.random.RandomState(seed=0).normal(size=1000)
|
|
b = [1, 1j, -1, -1j]
|
|
a = [1, 0.1]
|
|
y = utils.lfilter(x=x, b=b, a=a)
|
|
y1 = utils.lfilter(x=utils.lfilter(x=x, b=b, a=[1]), b=[1], a=a)
|
|
y2 = utils.lfilter(x=utils.lfilter(x=x, b=[1], a=a), b=b, a=[1])
|
|
assert_approx(y, y1)
|
|
assert_approx(y, y2)
|
|
|
|
z = utils.lfilter(x=y, b=a, a=[1])
|
|
z_ = utils.lfilter(x=x, b=b, a=[1])
|
|
assert_approx(z, z_)
|
|
|
|
|
|
def test_modem():
|
|
L = 1000
|
|
e = equalizer.Equalizer(config)
|
|
sent = e.train_symbols(L)
|
|
gain = config.Nfreq
|
|
x = e.modulator(sent) * gain
|
|
received = e.demodulator(x, L)
|
|
assert_approx(sent, received)
|
|
|
|
|
|
def test_signal():
|
|
length = 120
|
|
x = np.sign(RandomState(0).normal(size=length))
|
|
x[-20:] = 0 # make sure the signal has bounded support
|
|
den = np.array([1, -0.6, 0.1])
|
|
num = np.array([0.5])
|
|
y = utils.lfilter(x=x, b=num, a=den)
|
|
|
|
lookahead = 2
|
|
h = equalizer.train(
|
|
signal=y, expected=x, order=len(den), lookahead=lookahead)
|
|
assert dsp.norm(h[:lookahead]) < 1e-12
|
|
|
|
h = h[lookahead:]
|
|
assert_approx(h, den / num)
|
|
|
|
x_ = utils.lfilter(x=y, b=h, a=[1])
|
|
assert_approx(x_, x)
|