def R_wimp(E_th,E_max,m_chi,sigma_p=1.0e-45,\
Nuc=Params.Ar40,Loc=Params.GranSasso,\
HaloModel=Params.SHM,eff_on=False,eres_on=False):
nfine = 1000
Efine = logspace(-3.0, log10(200.0), nfine)
DM = Params.WIMP(m_chi, sigma_p)
# Calculate rate at day=67 to get ~average
dR = dRdE_wimp(Efine, array([(Jan1 + 67.0)]), DM, HaloModel, Nuc, Loc)
# Correct for efficiency
if eff_on:
dR *= LabFuncs.efficiency(Nuc, Efine)
# Smear by energy resolution
# if eres_on:
# dR = SmearE(Efine,dR,energyresolution(Nuc,Efine))
# Window
mask = (Efine < E_max) & (Efine > E_th)
R = trapz(dR[mask], Efine[mask])
return R
def R_Indiv(s, E_th, E_max, Nuc=Params.Ar40, eff_on=False, eres_on=False):
nfine = 1000
Efine = logspace(-3.0, log10(200.0), nfine)
# Load nu flux
data = loadtxt(nufile_dir + nuname[s] + nufile_root, delimiter=',')
E_nu = data[:, 0]
Flux = NuFlux[s] * data[:, 1]
sol = False
dR = dRdE_nu(Efine, Jan1 * ones(shape=nfine), sol, E_nu, Flux, Nuc=Nuc)
# Correct for efficiency
if eff_on:
dR *= LabFuncs.efficiency(Nuc, Efine)
# Smear by energy resolution
# if eres_on:
# dR = SmearE(Efine,dR,energyresolution(Nuc,Efine))
# Window
mask = (Efine < E_max) & (Efine > E_th)
R = trapz(dR[mask], Efine[mask])
return R