def test_result(self):
x = np.random.randn(100)
y = x - np.mean(x)
ynorm = np.sum(y**2)
acor = np.correlate(y, y, mode='same')[50:] / ynorm
self.assertTrue(all(acor == ConvergenceStats.autocorr(x)))
def test_result(self):
x = np.random.randn(100)
y = x - np.mean(x)
ynorm = np.sum(y ** 2)
acor = np.correlate(y, y, mode='same')[50:] / ynorm
self.assertTrue(all(acor == ConvergenceStats.autocorr(x)))
def test_normalisation(self):
x = np.random.randn(100)
acorr = ConvergenceStats.autocorr(x)
self.assertEqual(acorr[0], 1.)
def test_normalisation(self):
x = np.random.randn(100)
acorr = ConvergenceStats.autocorr(x)
self.assertEqual(acorr[0], 1.)