inj = PointSourceInjector(Gamma,
sinDec_bandwidth=.05,
src_dec=src_dec,
seed=0)
else:
inj = PointSourceInjector(Gamma,
sinDec_bandwidth=.05,
src_dec=src_dec,
theo_weight=modelweights['{}'.format(injweight)],
seed=0)
sensitivity = MultiPointSourceLLH.weighted_sensitivity(llhmodel,
src_ra=src_ra,
src_dec=src_dec,
alpha=.5,
beta=.9,
inj=inj,
trials={
'n_inj': [],
'TS': [],
'nsources': [],
'gamma': []
},
bckg_trials=bckg_trials,
eps=100.,
n_iter=1)
print('Sensitivity mu = ' + str(musens) + ', flux =' +
str(inj.mu2flux(musens)))
print('Discovery flux =' + str(mudisc) + ', flux =' + str(inj.mu2flux(mudisc)))
## Like in the background trials, we have to define which llhmodel to use.
if llhweight == 'uniform':
llh79 = data_multi.init79(energy=True)
llh59= data_multi.init59(energy=True)
llh40= data_multi.init40(energy=True)
else:
llh40= data_multi.init40(energy=True, weighting = modelweights['{}'.format(llhweight)])
llh79 = data_multi.init79(energy=True, weighting = modelweights['{}'.format(llhweight)])
llh59= data_multi.init59(energy=True, weighting = modelweights['{}'.format(llhweight)])
#We've loaded in the appropriate llh samples, now let's put them both in the blender (not sure about weighting)
samples = [llh40,llh59,llh79]
llhmodel = data_multi.multi_init(samples,energy=True)
##Remember, weighted sensitivity requires src dec in radians.#
##Now, I'll input my injection weighting scheme from the commandline. ##
if injweight == 'uniform':
inj = PointSourceInjector(Gamma, sinDec_bandwidth=.05, src_dec= src_dec, seed=0)
else:
inj = PointSourceInjector(Gamma, sinDec_bandwidth=.05, src_dec= src_dec, theo_weight = modelweights['{}'.format(injweight)], seed=0)
sensitivity = MultiPointSourceLLH.weighted_sensitivity(llhmodel,src_ra=src_ra,src_dec=src_dec,alpha=.5,beta=.9,inj=inj,trials={'n_inj':[],'TS':[],'nsources':[],'gamma':[]},bckg_trials=bckg_trials,eps=100.,n_iter=1)
print ('Sensitivity mu = ' + str(musens)+', flux =' + str(inj.mu2flux(musens)))
print ('Discovery flux =' + str(mudisc)+', flux =' +str(inj.mu2flux(mudisc)))