profile.scale_to_local_density()
position = SkyCoord(0.0, 0.0, frame="galactic", unit="deg")
geom = WcsGeom.create(binsz=0.05, skydir=position, width=3.0, coordsys="GAL")
# In[ ]:
jfactory = JFactory(geom=geom,
profile=profile,
distance=profiles.DMProfile.DISTANCE_GC)
jfact = jfactory.compute_jfactor()
# In[ ]:
jfact_map = WcsNDMap(geom=geom, data=jfact.value, unit=jfact.unit)
fig, ax, im = jfact_map.plot(cmap="viridis", norm=LogNorm(), add_cbar=True)
plt.title("J-Factor [{}]".format(jfact_map.unit))
# 1 deg circle usually used in H.E.S.S. analyses
sky_reg = CircleSkyRegion(center=position, radius=1 * u.deg)
pix_reg = sky_reg.to_pixel(wcs=geom.wcs)
pix_reg.plot(ax=ax, facecolor="none", edgecolor="red", label="1 deg circle")
plt.legend()
# In[ ]:
# NOTE: https://arxiv.org/abs/1607.08142 quote 2.67e21 without the +/- 0.3 deg band around the plane
total_jfact = pix_reg.to_mask().multiply(jfact).sum()
print("J-factor in 1 deg circle around GC assuming a "
"{} is {:.3g}".format(profile.__class__.__name__, total_jfact))
# Exclusion mask currently unused. Remove here or move to later in the tutorial?
# In[ ]:
target_position = SkyCoord(0, 0, unit="deg", frame="galactic")
on_radius = 0.2 * u.deg
on_region = CircleSkyRegion(center=target_position, radius=on_radius)
# In[ ]:
exclusion_mask = geom.to_image().region_mask([on_region], inside=False)
exclusion_mask = WcsNDMap(geom.to_image(), exclusion_mask)
exclusion_mask.plot();
# In[ ]:
get_ipython().run_cell_magic('time', '', 'maker = MapMaker(geom, offset_max="2 deg")\nmaps = maker.run(observations)\nprint(maps.keys())')
# In[ ]:
# The maps are cubes, with an energy axis.
# Let's also make some images:
images = maker.run_images()
# ### Compute images
#
# Exclusion mask currently unused. Remove here or move to later in the tutorial?
# In[ ]:
target_position = SkyCoord(0, 0, unit="deg", frame="galactic")
on_radius = 0.2 * u.deg
on_region = CircleSkyRegion(center=target_position, radius=on_radius)
# In[ ]:
exclusion_mask = geom.to_image().region_mask([on_region], inside=False)
exclusion_mask = WcsNDMap(geom.to_image(), exclusion_mask)
exclusion_mask.plot()
# In[ ]:
get_ipython().run_cell_magic(
'time', '',
'stacked = MapDataset.create(geom=geom)\nmaker = MapDatasetMaker(selection=["counts", "background", "exposure"])\nmaker_safe_mask = SafeMaskMaker(methods=["offset-max"], offset_max=2.5 * u.deg)\n\nfor obs in observations:\n cutout = stacked.cutout(obs.pointing_radec, width="5 deg")\n dataset = maker.run(cutout, obs)\n dataset = maker_safe_mask.run(dataset, obs)\n stacked.stack(dataset)'
)
# In[ ]:
# The maps are cubes, with an energy axis.
# Let's also make some images:
dataset_image = stacked.to_image()
images = {
