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.)