def CalcLikelihood(gsq, m_med, event_list):
#Poisson likelihood
No = len(event_list)
Ne = CalcNevents(gsq, m_med, tab=True)
PL = -Ne + No * np.log(Ne)
for i in range(No):
PL += np.log(exposure*CEvNS.differentialRate_CEvNS(event_list[i],\
A_Ge, Z_Ge, gsq, m_med,tab=True)/Ne)
return PL * 1.0 / Tchain
def GenerateEvents(N_exp):
No = np.random.poisson(lam=N_exp)
print " N_obs = ", No
events = np.zeros(No)
Rmax = CEvNS.differentialRate_CEvNS(E_min, A_Ge, Z_Ge)
#Get the inverse cumulative distribution
Evals = np.logspace(np.log10(E_min), np.log10(E_max), 100)
dRdE = np.vectorize(CEvNS.differentialRate_CEvNS)
Rvals = dRdE(Evals, A_Ge, Z_Ge)
Rcum = cumtrapz(Rvals, Evals, initial=0.0)
Rcum = Rcum / Rcum[-1]
fx = interp1d(Rcum, Evals)
xvals = np.random.rand(No)
return fx(xvals)
#Slow rejection method
"""
def CalcNevents(gsq=0.0, m_med=1000.0, tab=False):
integ = lambda x: CEvNS.differentialRate_CEvNS(x,\
A_Ge, Z_Ge, gsq, m_med, tab)
return exposure * quad(integ, E_min, E_max, epsrel=1e-4)[0]
#pl.loglog(Q_list, lnL)
#pl.axhline(3.84, linestyle=":")
#pl.show()
return np.min(Q_list[lnL > 3.84])
#----Main Procedure----
print " "
print "****************************"
print "* LimitCalculator.py *"
print "****************************"
print " "
print " Calculating Z-prime limits..."
print " NB: perturbativity limit is Q_Z'=", 12.0 * np.pi * A_Ge
"""
Qv = (A_Ge-Z_Ge)
G_FERMI = 1.1664e-5
SQRT2 = np.sqrt(2.0)
qsq = 2*0.9315*A_Ge
def G_V(QvNP, m_med):
return 1e6*(SQRT2/G_FERMI)*(QvNP/Qv)*1.0/(qsq + m_med*m_med)
m_medlist = np.logspace(0.0, 7.0)
Qlist = np.logspace(-10, np.log10(12.0*np.pi*A_Ge))
#Glist = G_V(12.0*np.pi*A_Ge, m_medlist)
#print m_medlist, Glist