import scipy.stats
import matplotlib.pyplot as plt
import numpy as np
from statepoint import StatePoint
# Create StatePoint object
sp1 = StatePoint('without-ufs.state')
sp2 = StatePoint('with-ufs.state')
# Calculate t-value for 95% two-sided CI
n = sp1.current_batch - sp1.n_inactive
t_value = scipy.stats.t.ppf(0.975, n - 1)
# Get uncertainties for without UFS
sp1.read_values()
unc1 = []
for s, s2 in sp1.tallies[0].values[:,0,:]:
s /= n
if s != 0.0:
relative_error = t_value*sqrt((s2/n - s*s)/(n-1))/s
unc1.append(relative_error)
# Get uncertainties for with UFS
sp2.read_values()
unc2 = []
for s, s2 in sp2.tallies[0].values[:,0,:]:
s /= n
if s != 0.0:
relative_error = t_value*sqrt((s2/n - s*s)/(n-1))/s
unc2.append(relative_error)
import scipy.stats
import matplotlib.pyplot as plt
import numpy as np
from statepoint import StatePoint
# Create StatePoint object
sp1 = StatePoint('without-ufs.state')
sp2 = StatePoint('with-ufs.state')
# Calculate t-value for 95% two-sided CI
n = sp1.current_batch - sp1.n_inactive
t_value = scipy.stats.t.ppf(0.975, n - 1)
# Get uncertainties for without UFS
sp1.read_values()
unc1 = []
for s, s2 in sp1.tallies[0].values[:, 0, :]:
s /= n
if s != 0.0:
relative_error = t_value * sqrt((s2 / n - s * s) / (n - 1)) / s
unc1.append(relative_error)
# Get uncertainties for with UFS
sp2.read_values()
unc2 = []
for s, s2 in sp2.tallies[0].values[:, 0, :]:
s /= n
if s != 0.0:
relative_error = t_value * sqrt((s2 / n - s * s) / (n - 1)) / s
unc2.append(relative_error)
