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.)