def test_fingerprint_correlation(fingerprints_data, observables):
obs1, obs2 = observables
T = fingerprints_data.transition_matrix
ts = timescales(T, k=4 if fingerprints_data.sparse else None)
R, D, L = rdl_decomposition(T, k=4 if fingerprints_data.sparse else None)
mu = fingerprints_data.stationary_distribution
tau = 7.5
if not fingerprints_data.sparse:
"""k=None, tau=1"""
acorr_amp = np.dot(mu * obs1, R) * np.dot(L, obs1)
tsn, acorr_ampn = fingerprint_correlation(T, obs1)
assert_allclose(tsn, ts)
assert_allclose(acorr_ampn, acorr_amp)
"""k=None, tau=7.5"""
tau = tau
tsn, acorr_ampn = fingerprint_correlation(T, obs1, tau=tau)
assert_allclose(tsn, tau * ts)
assert_allclose(acorr_ampn, acorr_amp)
"""k=4, tau=1"""
k = 4
acorr_amp = np.dot(mu * obs1, R[:, 0:k]) * np.dot(L[0:k, :], obs1)
tsn, acorr_ampn = fingerprint_correlation(T, obs1, k=k)
assert_allclose(tsn, ts[0:k])
assert_allclose(acorr_ampn, acorr_amp)
"""k=4, tau=7.5"""
tau = tau
tsn, acorr_ampn = fingerprint_correlation(T, obs1, k=k, tau=tau)
assert_allclose(tsn, tau * ts[0:k])
assert_allclose(acorr_ampn, acorr_amp)
"""Cross-correlation"""
if not fingerprints_data.sparse:
"""k=None, tau=1"""
corr_amp = np.dot(mu * obs1, R) * np.dot(L, obs2)
tsn, corr_ampn = fingerprint_correlation(T, obs1, obs2=obs2)
assert_allclose(tsn, ts)
assert_allclose(corr_ampn, corr_amp)
"""k=None, tau=7.5"""
tau = tau
tsn, corr_ampn = fingerprint_correlation(T, obs1, obs2=obs2, tau=tau)
assert_allclose(tsn, tau * ts)
assert_allclose(corr_ampn, corr_amp)
"""k=4, tau=1"""
corr_amp = np.dot(mu * obs1, R[:, 0:k]) * np.dot(L[0:k, :], obs2)
tsn, corr_ampn = fingerprint_correlation(T, obs1, obs2=obs2, k=k)
assert_allclose(tsn, ts[0:k])
assert_allclose(corr_ampn, corr_amp)
"""k=4, tau=7.5"""
tsn, corr_ampn = fingerprint_correlation(T, obs1, obs2=obs2, k=k, tau=tau)
assert_allclose(tsn, tau * ts[0:k])
assert_allclose(corr_ampn, corr_amp)
def test_fingerprint_correlation(self):
"""Autocorrelation"""
"""k=4, tau=1"""
k = self.k
acorr_amp = np.dot(self.mu * self.obs1, self.R) * np.dot(
self.L, self.obs1)
tsn, acorr_ampn = fingerprint_correlation(self.T, self.obs1, k=k)
assert_allclose(tsn, self.ts)
assert_allclose(acorr_ampn, acorr_amp)
"""k=4, tau=7.5"""
tau = self.tau
tsn, acorr_ampn = fingerprint_correlation(self.T,
self.obs1,
k=k,
tau=tau)
assert_allclose(tsn, tau * self.ts)
assert_allclose(acorr_ampn, acorr_amp)
"""Cross-correlation"""
"""k=4, tau=1"""
k = self.k
corr_amp = np.dot(self.mu * self.obs1, self.R) * np.dot(
self.L, self.obs2)
tsn, corr_ampn = fingerprint_correlation(self.T,
self.obs1,
obs2=self.obs2,
k=k)
assert_allclose(tsn, self.ts)
assert_allclose(corr_ampn, corr_amp)
"""k=4, tau=7.5"""
tau = self.tau
tsn, corr_ampn = fingerprint_correlation(self.T,
self.obs1,
obs2=self.obs2,
k=k,
tau=tau)
assert_allclose(tsn, tau * self.ts)
assert_allclose(corr_ampn, corr_amp)