def test_pol_rot(self, method1, method2, phi):
phi = np.pi / phi
fb = 40.e9
os = 2
fs = os * fb
N = 2**16
beta = 0.9
mu1 = 0.1e-2
mu2 = 0.1e-2
M = 32
s = signals.SignalQAMGrayCoded(M, N, nmodes=2, fb=fb)
s = s.resample(fs, beta=beta, renormalise=True)
s = impairments.rotate_field(s, phi)
sout, wxy, err = equalisation.dual_mode_equalisation(
s, (mu1, mu2),
Ntaps=5,
Niter=(3, 3),
methods=(method1, method2),
adaptive_stepsize=(True, True))
sout = helpers.normalise_and_center(sout)
ser = sout.cal_ser()
#plt.plot(sout[0].real, sout[0].imag, 'r.')
#plt.plot(sout[1].real, sout[1].imag, 'b.')
#plt.show()
if ser.mean() > 0.5:
ser = sout[::-1].cal_ser()
npt.assert_allclose(ser, 0)
def test_pol_rot(self, method, phi):
phi = np.pi / phi
fb = 40.e9
os = 2
fs = os * fb
N = 2**16
beta = 0.1
mu = 0.1e-2
M = 4
ntaps = 5
s = signals.SignalQAMGrayCoded(M, N, nmodes=2, fb=fb)
s = s.resample(fs, beta=beta, renormalise=True)
s = impairments.rotate_field(s, phi)
wxy, err = equalisation.equalise_signal(s,
mu,
Niter=3,
Ntaps=ntaps,
method=method,
adaptive_stepsize=True,
avoid_cma_sing=False)
sout = equalisation.apply_filter(s, wxy)
#plt.plot(sout[0].real, sout[0].imag, '.r')
#plt.show()
ser = sout.cal_ser()
#if ser.mean() > 0.5:
#ser = sout[::-1].cal_ser
npt.assert_allclose(ser, 0)
def test_rotate_field(self):
s2 = impairments.rotate_field(self.s, np.pi / 3)
assert type(self.s) is type(s2)
def test_rotate_field_attr(self, attr):
s2 = impairments.rotate_field(self.s, np.pi / 3)
assert getattr(self.s, attr) is getattr(s2, attr)
def test_rotate_field(self, dtype):
s = signals.ResampledQAM(16, 2**14, fs=2, nmodes=2, dtype=dtype)
s2 = impairments.rotate_field(s, np.pi / 3)
assert np.dtype(dtype) is s2.dtype