def test_with_correlated_data_multiple_replica(self): r"""Check the :class:`puwr.tauint` method with the :class:`puwr.correlated_data` method. Note that this is a statistical test with random numbers. We test for a :math:`3\sigma` deviation here, which is unlikely but not impossible. If this test fails, re-run a few times before making any conclusions.""" fails = 0 for known_tau in np.linspace(2,20,10): data = [[correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0]]] mean, err, tau, dtau = tauint(data, 0) if tau - 3*dtau > known_tau or \ tau + 3*dtau < known_tau: print tau - known_tau, dtau fails += 1 self.assertGreaterEqual(0, fails)
def test_with_correlated_data_multiple_replica(self): r"""Check the :class:`puwr.tauint` method with the :class:`puwr.correlated_data` method. Note that this is a statistical test with random numbers. We test for a :math:`3\sigma` deviation here, which is unlikely but not impossible. If this test fails, re-run a few times before making any conclusions.""" fails = 0 for known_tau in np.linspace(2, 20, 10): data = [[ correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0] ]] mean, err, tau, dtau = tauint(data, 0) if tau - 3*dtau > known_tau or \ tau + 3*dtau < known_tau: print tau - known_tau, dtau fails += 1 self.assertGreaterEqual(0, fails)
def test_secondary_multiple_replica_product(self): """Test using the product of two observables.""" fails = 0 for known_tau in np.linspace(2,20,10): data = [[correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0]], [correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0]]] mean, err, tau, dtau = tauint(data, lambda x, y: x * y) if tau - 3*dtau > known_tau or \ tau + 3*dtau < known_tau: print tau - known_tau, dtau fails += 1 self.assertGreaterEqual(0, fails)
def test_secondary_multiple_replica_product(self): """Test using the product of two observables.""" fails = 0 for known_tau in np.linspace(2, 20, 10): data = [[ correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0] ], [ correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0], correlated_data(known_tau)[0][0] ]] mean, err, tau, dtau = tauint(data, lambda x, y: x * y) if tau - 3*dtau > known_tau or \ tau + 3*dtau < known_tau: print tau - known_tau, dtau fails += 1 self.assertGreaterEqual(0, fails)