# In[ ]:
pwl = PowerLaw(index=2.3,
amplitude=1e-11 * u.Unit("cm-2 s-1 TeV-1"),
reference=1 * u.TeV)
print(pwl)
# In[ ]:
livetime = 2 * u.h
sim = SpectrumSimulation(aeff=aeff,
edisp=edisp,
source_model=pwl,
livetime=livetime)
sim.simulate_obs(seed=2309, obs_id=1)
print(sim.obs)
# In[ ]:
fit = SpectrumFit(obs_list=sim.obs, model=pwl.copy(), stat="cash")
fit.fit_range = [1, 10] * u.TeV
fit.run()
print(fit.result[0])
# ## Include background
#
# In this section we will include a background component. Furthermore, we will also simulate more than one observation and fit each one individuallt in order to get average fit results.
# In[ ]:
edisp = edisp.to_energy_dispersion(offset=offset)
aeff = aeff.to_effective_area_table(offset=offset)
#fig, axes = plt.subplots(1, 2, figsize=(12, 6))
#edisp.plot_matrix(ax=axes[0])
#aeff.plot(ax=axes[1])
#plt.show()
aeff.lo_threshold = lo_threshold
aeff.hi_threshold = hi_threshold
sim = SpectrumSimulation(aeff=aeff,
edisp=edisp,
source_model=model,
livetime=livetime)
sim.simulate_obs(seed=42, obs_id=0)
sim.obs.peek()
print sim.obs
plt.show()
fit = SpectrumFit(obs_list=sim.obs, model=model, stat='cash')
fit.run()
result = fit.result[0]
print result
energy_range = [0.1, 100] * u.TeV
model.plot(energy_range=energy_range, energy_power=2)
result.model.plot(energy_range=energy_range, energy_power=2)
result.model.plot_error(energy_range=energy_range, energy_power=2)