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from scipy import signal
import numpy as np
import src.gen_source as gs
import src.dab_util as du
def gen_test_signals(oversampling=4, sample_offset_float=0):
off = int(sample_offset_float)
phi_samples = sample_offset_float - off
phi = phi_samples*360/oversampling
s1 = np.zeros((1024))
s1[256:768] = gs.gen_sin(512, oversampling, 0)
s2 = np.zeros((1024))
s2[256+off:768+off] = gs.gen_sin(512, oversampling, phi)
return s1, s2
def test_phase_offset(lag_function, tol):
def r():
return np.random.rand(1)*100-50
res = []
for i in range(100):
off = r()
s1, s2 = gen_test_signals(
oversampling=4, sample_offset_float=off)
off_meas = lag_function(s2, s1)
res.append(np.abs(off-off_meas)<tol)
return np.mean(res)
for n_up in [1, 2, 3, 4, 7, 8, 16]:
correct_ratio = test_phase_offset(lambda x,y: du.lag_upsampling(x,y,n_up), tol=1./n_up)
print("%.1f%% of the tested offsets were measured within tolerance %.4f for n_up = %d" % (correct_ratio * 100, 1./n_up, n_up))
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