def test_acorr(self):
cor1 = xcorrf(self.data1, self.data1, self.N // 4, oneside=True)
cor2 = acorrf(self.data1, self.N // 4)
# from pylab import plot, show
# plot(cor1)
# plot(cor2)
# show()
np.testing.assert_array_almost_equal(cor1, cor2, 3)
self.assertTrue((cor2[0] - 1) ** 2 < 1e-5)
def test_acorr(self):
cor1 = xcorrf(self.data1, self.data1, self.N // 4, oneside=True)
cor2 = acorrf(self.data1, self.N // 4)
# from pylab import plot, show
# plot(cor1)
# plot(cor2)
# show()
np.testing.assert_array_almost_equal(cor1, cor2, 3)
self.assertTrue((cor2[0] - 1)**2 < 1e-5)
def test_xcorr_acorrf(self):
data1 = np.sin(np.arange(1001) * 2.1 * np.pi / 500.)
cor1 = acorrt(data1, 1024, oneside=True, clipdata=False)
cor2 = acorrf(data1, 1024, oneside=True, clipdata=False)
# from pylab import plot, show, subplot, legend
# subplot(211)
# plot(data1)
# subplot(212)
# plot(cor1, label='acorrt')
# plot(cor2, label='acorrf')
# legend()
# show()
print (np.sum((cor1 - cor2) ** 2) / len(cor1)) ** 0.5
self.assertTrue((np.sum((cor1 - cor2) ** 2) / len(cor1)) ** 0.5 < 0.1)
def test_xcorr_acorrf(self):
data1 = np.sin(np.arange(1001) * 2.1 * np.pi / 500.)
cor1 = acorrt(data1, 1024, oneside=True, clipdata=False)
cor2 = acorrf(data1, 1024, oneside=True, clipdata=False)
# from pylab import plot, show, subplot, legend
# subplot(211)
# plot(data1)
# subplot(212)
# plot(cor1, label='acorrt')
# plot(cor2, label='acorrf')
# legend()
# show()
print(np.sum((cor1 - cor2)**2) / len(cor1))**0.5
self.assertTrue((np.sum((cor1 - cor2)**2) / len(cor1))**0.5 < 0.1)
