def calculate_moments(self, storage: SampleStorageHDF,
qspec: QuantitySpec):
"""
Calculate moments of given quantity for all times.
:param storage: Sample HDF storage
:param qspec: quantity given by QuantitySpec
:return: moments means estimates, their variances; tuple of 2 np.arrays of length 3
"""
n_moments = 3
means = []
vars = []
for time_id in range(len(qspec.times)):
true_domain = QuantityEstimate.estimate_domain(storage,
qspec,
time_id,
quantile=0.01)
# moments_fn = moments.Legendre(n_moments, true_domain)
# moments_fn = moments.Monomial(n_moments, true_domain)
# compute mean in real values (without transform to ref domain)
# mean_moment_fn = moments.Monomial.factory(2, domain=true_domain, ref_domain=true_domain, safe_eval=False)
# q_estimator = QuantityEstimate(sample_storage=storage, sim_steps=self.step_range,
# qspec=qspec, time_id=time_id)
# m, v = q_estimator.estimate_moments(mean_moment_fn)
#
# # The first moment is in any case 1 and its variance is 0
# assert m[0] == 1
# assert v[0] == 0
# compute variance in real values (center by computed mean)
# mean_moment_fn = moments.Monomial.factory(3, center=m[1])
mean_moment_fn = moments.Monomial.factory(3,
domain=true_domain,
ref_domain=true_domain,
safe_eval=False)
q_estimator = QuantityEstimate(sample_storage=storage,
sim_steps=self.step_range,
qspec=qspec,
time_id=time_id)
mm, vv = q_estimator.estimate_moments(mean_moment_fn)
# The first moment is in any case 1 and its variance is 0
assert np.isclose(mm[0], 1, atol=1e-10)
assert vv[0] == 0
# assert np.isclose(mm[1], 0, atol=1e-10)
# means.append([1, m[1], mm[2]])
# vars.append([0, v[1], vv[2]])
means.append(mm)
vars.append(vv)
# print("t = ", qspec.times[time_id], " means ", mm[1], mm[2])
# print("t = ", qspec.times[time_id], " vars ", vv[1], vv[2])
return np.array(means), np.array(vars)
def set_moments(self, sample_storage):
n_moments = 5
true_domain = QuantityEstimate.estimate_domain(sample_storage, quantile=0.01)
return Legendre(n_moments, true_domain)