)
background_estimator.run()
# In[ ]:
# print(background_estimator.result[0])
# In[ ]:
plt.figure(figsize=(8, 8))
background_estimator.plot()
# ## Source statistic
#
# Next we're going to look at the overall source statistics in our signal region. For more info about what debug plots you can create check out the [ObservationSummary](http://docs.gammapy.org/dev/api/gammapy.data.ObservationSummary.html#gammapy.data.ObservationSummary) class.
# In[ ]:
stats = []
for obs, bkg in zip(obs_list, background_estimator.result):
stats.append(ObservationStats.from_obs(obs, bkg))
print(stats[1])
background_estimator = ReflectedRegionsBackgroundEstimator(
observations=observations,
on_region=on_region,
exclusion_mask=exclusion_mask,
)
background_estimator.run()
# In[ ]:
# print(background_estimator.result[0])
# In[ ]:
plt.figure(figsize=(8, 8))
background_estimator.plot(add_legend=True)
# ## Source statistic
#
# Next we're going to look at the overall source statistics in our signal region. For more info about what debug plots you can create check out the [ObservationSummary](https://docs.gammapy.org/0.10/api/gammapy.data.ObservationSummary.html#gammapy.data.ObservationSummary) class.
# In[ ]:
stats = []
for obs, bkg in zip(observations, background_estimator.result):
stats.append(ObservationStats.from_observation(obs, bkg))
print(stats[1])
obs_summary = ObservationSummary(stats)
fig = plt.figure(figsize=(10, 6))
xref=image_center.l.deg,
yref=image_center.b.deg,
proj='TAN',
coordsys='GAL',
)
exclusion_mask = exclusion_mask.region_mask(exclusion_region)
exclusion_mask.data = 1. - exclusion_mask.data
background_estimator = ReflectedRegionsBackgroundEstimator(
obs_list=obs_list, on_region=on_region, exclusion_mask=exclusion_mask)
background_estimator.run()
plt.figure(figsize=(8, 8))
bkg_ex_plot = background_estimator.plot()
plt.show(bkg_ex_plot)
#######################
stats = []
for obs, bkg in zip(obs_list, background_estimator.result):
stats.append(ObservationStats.from_obs(obs, bkg))
print(stats[1])
obs_summary = ObservationSummary(stats)
fig = plt.figure(figsize=(10, 6))
ax1 = fig.add_subplot(121)
aa = obs_summary.plot_excess_vs_livetime(ax=ax1)
ax2 = fig.add_subplot(122)