def test_frac_time_shift_with_random(self):
""" Test frac_time_shift with a random signal"""
N = 1024
p, q = (7, 6) # resampling parameters
b, a = scipy.signal.butter(10, .25)
shifts = (0.5, 1 / 6, numpy.random.uniform(low=-5, high=+5))
for shift in shifts:
noise = numpy.pad(numpy.random.rand(N // 2), (N // 4, N // 4))
filt_noise = scipy.signal.filtfilt(b, a, noise)
res1 = pb.frac_time_shift(
scipy.signal.resample_poly(filt_noise, p, q), p / q * shift)
res2 = scipy.signal.resample_poly(
pb.frac_time_shift(filt_noise, shift), p, q)
error = numpy.max(numpy.abs(res1 - res2))
# ax1 = plt.subplot(2, 2, 1)
# ax1.plot(res1, label='resamp/shift')
# ax1.plot(res2, '.', label='shift/resamp')
#
# ax1.legend()
# ax1.grid()
#
# ax2 = plt.subplot(2, 2, 2)
# ax2.plot(numpy.abs(res1-res2))
# ax2.grid()
# plt.show()
self.assertLess(error, 10**pb.LOG10_REJECTION)
def test_frac_time_shift_output_size(self):
""" Test frac_time_shift: check input and output sizes match"""
N = 1024
shift = numpy.random.uniform(low=-5, high=+5)
shifted = pb.frac_time_shift(numpy.zeros(N), shift)
self.assertEqual(shifted.size, N)
def test_frac_time_shift_with_sinus(self):
""" Test frac_time_shift with sinusoidal signal"""
N = 1024
shifts = (0.5, 1 / 6, numpy.random.uniform(low=-5, high=+5))
time = numpy.arange(-N / 2, N / 2)
sigma = N / 4
for shift in shifts:
time_shifted = time - shift
# error = []
for f in numpy.arange(
math.floor(
(pb.STOPBAND_CUTOFF_F - pb.ROLL_OFF_WIDTH) * N)) / N:
phi = 2 * math.pi * numpy.random.rand()
signal = sinegauss(time, sigma, f, phi)
estimate_shifted = pb.frac_time_shift(signal, shift)
exact_shifted = sinegauss(time_shifted, sigma, f, phi)
error = numpy.max(numpy.abs(estimate_shifted - exact_shifted))
# error.append(numpy.max(numpy.abs(estimate_shifted-exact_shifted)))
self.assertLess(error, 10**pb.LOG10_REJECTION)