sens = [[] for _ in src_res]
fracs = [[] for _ in src_res]
disc_pots = [[] for _ in src_res]
sens_e = [[] for _ in src_res]
disc_e = [[] for _ in src_res]
labels = []
for i, (f_type, res) in enumerate(sorted(src_res.items())):
for (length, rh_dict) in sorted(res.items()):
rh = ResultsHandler(rh_dict)
inj_time = length * (60 * 60 * 24)
astro_sens, astro_disc = rh.astro_values(
rh_dict["inj_dict"]["injection_energy_pdf"])
e_key = "Mean Luminosity (erg/s)"
sens[i].append(rh.sensitivity * inj_time)
disc_pots[i].append(rh.disc_potential * inj_time)
sens_e[i].append(astro_sens[e_key] * inj_time)
disc_e[i].append(astro_disc[e_key] * inj_time)
fracs[i].append(length)
labels.append(f_type)
# plt.plot(fracs, disc_pots, linestyle="--", color=cols[i])
for j, [fluence, energy] in enumerate([[sens, sens_e], [disc_pots, disc_e]]):
plt.figure()
["injection_energy_pdf"]["e_min_gev"])
e_max_gev.append(rh_dict["inj_dict"]
["injection_energy_pdf"]["e_max_gev"])
# sensitivity/dp normalized per flux normalization GeV-1 cm-2 s-1
sens.append(rh.sensitivity)
sens_err_low.append(rh.sensitivity_err[0])
sens_err_upp.append(rh.sensitivity_err[1])
disc_pot.append(rh.disc_potential)
disc_ts_threshold.append(rh.disc_ts_threshold)
sens_n.append(rh.sensitivity * rh.flux_to_ns)
disc_pot_n.append(rh.disc_potential * rh.flux_to_ns)
key = "Energy Flux (GeV cm^{-2} s^{-1})" # old version: "Total Fluence (GeV cm^{-2} s^{-1})"
astro_sens, astro_disc = rh.astro_values(
rh_dict["inj_dict"]["injection_energy_pdf"])
sens_livetime.append(
astro_sens[key]) # fluence=integrated over energy
disc_pots_livetime.append(astro_disc[key])
# Nu energy flux integrated between 100GeV and 10PeV,
# indipendently from the e_min_gev, e_max_gev of the injection
rh_dict["inj_dict"]["injection_energy_pdf"][
"e_min_gev"] = 100
rh_dict["inj_dict"]["injection_energy_pdf"][
"e_max_gev"] = 1e7
astro_sens_100GeV10PeV, astro_disc_100GeV10PeV = rh.astro_values(
rh_dict["inj_dict"]["injection_energy_pdf"])
sens_livetime_100GeV10PeV.append(
astro_sens_100GeV10PeV[key]
) # fluence=integrated over energy
src_1_frac = old_div(min(catalogue["Distance (Mpc)"])**-2,np.sum(
catalogue["Distance (Mpc)"] ** -2
))
for i, (f_type, res) in enumerate(sorted(src_res.items())):
for (length, rh_dict) in sorted(res.items()):
try:
rh = ResultsHandler(rh_dict)
# Convert flux to fluence and source energy
inj_time = length * 60 * 60 * 24
astro_sens, astro_disc = rh.astro_values(
rh_dict["inj kwargs"]["Injection Energy PDF"])
key = "Total Fluence (GeV cm^{-2} s^{-1})"
e_key = "Mean Luminosity (erg/s)"
sens[i].append(astro_sens[key] * inj_time)
disc_pots[i].append(astro_disc[key] * inj_time)
sens_e[i].append(astro_sens[e_key] * inj_time)
disc_e[i].append(astro_disc[e_key] * inj_time)
fracs[i].append(length)
except OSError:
pass