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)