def estimate_reflected(self, EXCLUSION_FILE, size):
#just extracts the reflected background
on_size=0.11 * u.deg #0.11 for point source cuts...
allsky_mask = SkyImage.read(EXCLUSION_FILE)
exclusion_mask = allsky_mask.cutout(position=self.obspos,size=size)
on_region=CircleSkyRegion(self.obspos,on_size)
background_estimator = ReflectedRegionsBackgroundEstimator(obs_list=self.obslist, on_region=on_region, exclusion_mask = exclusion_mask)
background_estimator.run()
return background_estimator.result[0]
proj="TAN",
coordsys="GAL")
mask = exclusion_mask.geom.region_mask([exclusion_region], inside=False)
exclusion_mask.data = mask
exclusion_mask.plot()
# ## Estimate background
#
# Next we will manually perform a background estimate by placing [reflected regions](https://docs.gammapy.org/0.10/background/reflected.html) around the pointing position and looking at the source statistics. This will result in a [gammapy.background.BackgroundEstimate](https://docs.gammapy.org/0.10/api/gammapy.background.BackgroundEstimate.html) that serves as input for other classes in gammapy.
# In[ ]:
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
)
mask = exclusion_mask.geom.region_mask([exclusion_region], inside=False)
exclusion_mask.data = mask
exclusion_mask.plot()
# ## Estimate background
#
# Next we will manually perform a background estimate by placing [reflected regions](http://docs.gammapy.org/dev/background/reflected.html) around the pointing position and looking at the source statistics. This will result in a [gammapy.background.BackgroundEstimate](http://docs.gammapy.org/dev/api/gammapy.background.BackgroundEstimate.html) that serves as input for other classes in gammapy.
# In[ ]:
background_estimator = ReflectedRegionsBackgroundEstimator(
obs_list=obs_list, on_region=on_region, exclusion_mask=exclusion_mask
)
background_estimator.run()
# In[ ]:
# print(background_estimator.result[0])
# In[ ]:
plt.figure(figsize=(8, 8))
allsky_mask = SkyImage.read(EXCLUSION_FILE)
exclusion_mask = allsky_mask.cutout(
position=crab,
size=Angle('6 deg'),
)
EXCLUSION_FILE = '$GAMMAPY_EXTRA/datasets/exclusion_masks/tevcat_exclusion.fits'
allsky_mask = SkyImage.read(EXCLUSION_FILE)
exclusion_mask = allsky_mask.cutout(
position=crab,
size=Angle('6 deg'),
)
from gammapy.background.reflected import ReflectedRegionsBackgroundEstimator
get_ipython().magic(u'pinfo ReflectedRegionsBackgroundEstimator')
on_region=CircleSkyRegion(crab,0.15 * u.deg)
background_estimator = ReflectedRegionsBackgroundEstimator(obs_list=fakerun, on_region=on_region, exclusion_mask = exclusion_mask)
background_estimator.run()
get_ipython().magic(u'pinfo background_estimator.run')
get_ipython().magic(u'pinfo background_estimator.result')
fakerun.obs_id
background_estimator.process()
background_estimator.process(fakerun)
background_estimator.result
background_estimator.result[0]
background_estimator.result
print background_estimator.result
plt.figure(figsize=(8,8))
background_estimator.plot()
len(fakerun)
background_estimator.obs_list
print background_estimator.obs_list
b=a
plt.plot(a,b)
plt.show()
import matplotlib.pyplot as plt
ana.spectrum_result.plot(
energy_range=ana.fit.fit_range,
energy_power=2,
flux_unit='erg-1 cm-2 s-1',
fig_kwargs=dict(figsize = (8,8)),
)
plt.show()
plt.plot()
x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)
plt.show()
allsky_mask = SkyImage.read(EXCLUSION_FILE)
exclusion_mask = allsky_mask.cutout(
position=on_region.center,
size=Angle('6 deg'),
)
background_estimator = ReflectedRegionsBackgroundEstimator(obs_list=crablist,
on_region=on_region, exclusion_mask = exclusion_mask)
background_estimator.run()
print(background_estimator.result[0])
plt.figure(figsize=(8,8))
background_estimator.plot()
plt.plot()
plt.show()
get_ipython().magic(u'save testfit.py 1-194')