def test_altes(self):
ideal = np.array([
0.00200822, -0.21928398, 0.66719239, 0.66719239, -0.17666382,
-0.17009953, -0.038399, -0.00083597
])
actual = misc.altes(8, 0.1, 0.5)
np.testing.assert_allclose(ideal, actual, atol=1e-8, rtol=1e-8)
tau_start, tau_end = -(n - 1) / 2, (n + 1) / 2
lag = np.arange(tau_start, tau_end)
taucol = lag.shape[0]
if n_fbins is None:
n_fbins = signal.shape[0]
naf = np.zeros((n_fbins, taucol), dtype=complex)
for icol in range(taucol):
taui = lag[icol]
t = np.arange(abs(taui), n - abs(taui))
naf[t, icol] = signal[t + taui] * np.conj(signal[t - taui])
naf = np.fft.fft(naf, axis=0)
_ix1 = np.arange((n_fbins + (n_fbins % 2)) / 2, n_fbins)
_ix2 = np.arange((n_fbins + (n_fbins % 2)) / 2)
_xi1 = -(n_fbins - (n_fbins % 2)) / 2
_xi2 = ((n_fbins + (n_fbins % 2)) / 2 - 1)
xi = np.arange(_xi1, _xi2 + 1, dtype=float) / n_fbins
naf = naf[np.hstack((_ix1, _ix2)), :]
return naf, lag, xi
if __name__ == '__main__':
from tftb.generators.misc import altes
sig = altes(128, 0.1, 0.45)
waf, tau, theta = wide_band(sig)
from matplotlib.pyplot import contour, show
contour(tau, theta, np.abs(waf) ** 2)
show()
lag = np.arange(tau_start, tau_end)
taucol = lag.shape[0]
if n_fbins is None:
n_fbins = signal.shape[0]
naf = np.zeros((n_fbins, taucol), dtype=complex)
for icol in range(taucol):
taui = int(lag[icol])
t = np.arange(abs(taui), n - abs(taui)).astype(int)
naf[t, icol] = signal[t + taui] * np.conj(signal[t - taui])
naf = np.fft.fft(naf, axis=0)
_ix1 = np.arange((n_fbins + (n_fbins % 2)) // 2, n_fbins)
_ix2 = np.arange((n_fbins + (n_fbins % 2)) // 2)
_xi1 = -(n_fbins - (n_fbins % 2)) // 2
_xi2 = ((n_fbins + (n_fbins % 2)) // 2 - 1)
xi = np.arange(_xi1, _xi2 + 1, dtype=float) / n_fbins
naf = naf[np.hstack((_ix1, _ix2)), :]
return naf, lag, xi
if __name__ == '__main__':
from tftb.generators.misc import altes
sig = altes(128, 0.1, 0.45)
waf, tau, theta = wide_band(sig)
from matplotlib.pyplot import contour, show
contour(tau, theta, np.abs(waf)**2)
show()
def test_altes(self):
ideal = np.array([0.00200822, -0.21928398, 0.66719239, 0.66719239,
-0.17666382, -0.17009953, -0.038399, -0.00083597])
actual = misc.altes(8, 0.1, 0.5)
np.testing.assert_allclose(ideal, actual, atol=1e-8, rtol=1e-8)
