def get_sens(ana,
ra,
sindec,
ext=np.radians(0),
llh_ext=None,
cut_n_sigma=None,
sigsub=False,
gamma=2,
batch_size=500):
src = cy.utils.Sources(ra=0, dec=np.arcsin(sindec), extension=ext)
flux = hyp.PowerLawFlux(gamma)
tr = get_tr(src=src,
ana=ana,
ext=ext,
llh_ext=llh_ext,
flux=flux,
cut_n_sigma=cut_n_sigma,
sigsub=sigsub)
bg = cy.dists.Chi2TSD(tr.get_many_fits(1000))
sens = tr.find_n_sig(bg.median(),
0.9,
batch_size=batch_size,
max_batch_size=1000,
tol=0.03,
coverage=2)
sens['flux'] = tr.to_E2dNdE(sens['n_sig'], E0=100, unit=1e3)
return sens['flux']
def get_tr(src,
ana=ana7,
ext=np.radians(0),
llh_ext=None,
flux=hyp.PowerLawFlux(2),
inj=True,
use_energy=True,
cut_n_sigma=None,
sigsub=False,
_fit_null=True,
mp_cpus=mp_cpus):
llh_ext = ext if llh_ext is None else llh_ext
llh_src = cy.utils.Sources(ra=src.ra, dec=src.dec, extension=llh_ext)
if cut_n_sigma is None:
cut_n_sigma = 5 if llh_ext < np.radians(3) else 3
# get_llh needs the src list
llh_kw = dict(src=llh_src, cut_n_sigma=cut_n_sigma, sigsub=sigsub)
# get_injs needs the src list and signal spectrum
inj_kw = dict(src=src,
llh_src=llh_src,
flux=flux,
cut_n_sigma=cut_n_sigma,
inj=inj)
# trial.get_trial_runner loops over sub analyses and gives a single TrialRunner
return trial.get_trial_runner(ana,
get_llh,
get_injs,
llh_kw=llh_kw,
inj_kw=inj_kw,
mp_cpus=mp_cpus)
def get_tr (src, ana=ana7, flux=hyp.PowerLawFlux (2), inj=True, use_energy=True, cut_n_sigma=5, sigsub=False, _fit_null=True, mp_cpus=mp_cpus):
# get_llh needs the src list
llh_kw = dict (src=src, sigsub=sigsub)
# get_injs needs the src list and signal spectrum
inj_kw = dict (src=src, flux=flux, cut_n_sigma=cut_n_sigma, inj=inj)
# trial.get_trial_runner loops over sub analyses and gives a single TrialRunner
return trial.get_trial_runner (
ana, get_llh, get_injs, llh_kw=llh_kw, inj_kw=inj_kw, mp_cpus=mp_cpus)
