def run_zbi_stat(self):
n_on = self.observation()
mu_b_hat = self.background
sigma_b = self.fullunc()
tau = mu_b_hat / (sigma_b * sigma_b)
n_off = tau * mu_b_hat
P_Bi = TMath.BetaIncomplete(1. / (1. + tau), n_on, n_off + 1)
Z_Bi = math.sqrt(2.) * TMath.ErfInverse(1 - 2. * P_Bi)
return str(round(Z_Bi, 4))
def getZbi(n_on, n_off, tau):
P_Bi = TMath.BetaIncomplete(1. / (1. + tau), n_on, n_off + 1)
Z_Bi = TMath.Sqrt(2) * TMath.ErfInverse(1 - 2 * P_Bi)
return (Z_Bi)
def getPbi(n_on, n_off, tau):
P_Bi = TMath.BetaIncomplete(1. / (1. + tau), n_on, n_off + 1)
return (P_Bi)
# Generate npoints randomly with importance sampling
npoints = 1000000
xg0 = xg00 = 0
for n1 in range(npoints):
#here do the calculation with importance sampling
x0 = xmin**gRandom.Uniform()
weight = x0*log(1/xmin)
# here do the calculation using linear sampling
# x0 = xmin+(1-xmin)*gRandom.Uniform()
# weight = 1-xmin
f = g0(x0)
ff = weight*f
xg0 += ff
xg00 += ff**2
# Calculate the MC integral
xg0 /= npoints
xg00 /= npoints
sigma2 = xg00 - xg0*xg0
error = sqrt(sigma2/npoints)
print " integral for g(x) = (1-x)**5/x is: ",xg0,"+/-", error
# Get the exact value using incomplete beta function [https://en.wikipedia.org/wiki/Beta_function]
x = 1-xmin
a = 5
b = -0.9999999999
print "Exact value ", TMath.BetaIncomplete(x, a+1, b+1) * TMath.Beta(a+1, b+1)
# Generate npoints randomly with importance sampling
xg0 = xg00 = 0
for n1 in range(npoints):
# here do the calculation with importance sampling
x0 = xmin**gRandom.Uniform()
weight = x0 * log(1 / xmin)
# here do the calculation using linear sampling
# x0 = xmin+(1-xmin)*gRandom.Uniform()
# weight = 1-xmin
f = g0(x0)
ff = weight * f
xg0 += ff
xg00 += ff**2
# Calculate the MC integral
xg0 /= npoints
xg00 /= npoints
sigma2 = xg00 - xg0 * xg0
error = sqrt(sigma2 / npoints)
print(" integral for g(x) = (1-x)**5/x is: ", xg0, "+/-", error)
# Get the exact value using incomplete beta function [https://en.wikipedia.org/wiki/Beta_function]
x = 1 - xmin
a = 5
b = -0.9999999999
print("Exact value ",
TMath.BetaIncomplete(x, a + 1, b + 1) * TMath.Beta(a + 1, b + 1))
