This is a fixed-text formatted version of a Jupyter notebook

H.E.S.S. with Gammapy

H.E.S.S. is an array of gamma-ray telescopes located in Namibia. Gammapy is regularly used and fully supports H.E.S.S. high level data analysis, after export to the current open data level 3 format.

The H.E.S.S. data is private, and H.E.S.S. analysis is mostly documented and discussed at and in H.E.S.S.-internal communication channels. However, in 2018, a small sub-set of archival H.E.S.S. data was publicly released, called the H.E.S.S. DL3 DR1, the data level 3, data release number 1. This dataset is 50 MB in size and is used in many Gammapy analysis tutorials, and can be downloaded via gammapy download.

This notebook is a quick introduction to this specific DR1 release. It briefly describes H.E.S.S. data and instrument responses and show a simple exploration of the data with the creation of theta-squared plot.

H.E.S.S. members can find details on the DL3 FITS production on this Confluence page and access more detailed tutorials in this repository


This is how to access data and IRFs from the H.E.S.S. data level 3, data release 1.

%matplotlib inline
import matplotlib.pyplot as plt
from astropy.coordinates import SkyCoord
import astropy.units as u
from import DataStore
from gammapy.maps import MapAxis
from gammapy.makers.utils import make_theta_squared_table
from gammapy.visualization import plot_theta_squared_table
data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1")
Data store:
HDU index table:
BASE_DIR: /home/runner/work/gammapy-docs/gammapy-docs/gammapy-datasets/hess-dl3-dr1
Rows: 630
OBS_ID: 20136 -- 47829
HDU_TYPE: ['aeff', 'bkg', 'edisp', 'events', 'gti', 'psf']
HDU_CLASS: ['aeff_2d', 'bkg_3d', 'edisp_2d', 'events', 'gti', 'psf_table']

Observation table:
Observatory name: 'N/A'
Number of observations: 105

data_store.obs_table[:2][["OBS_ID", "DATE-OBS", "RA_PNT", "DEC_PNT", "OBJECT"]]
ObservationTable length=2
obs = data_store.obs(23523)
[7]:[0, 2.5] * u.deg).peek()
/usr/share/miniconda/envs/gammapy-dev/lib/python3.7/site-packages/astropy/visualization/wcsaxes/ MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.
  return super().imshow(X, *args, origin=origin, **kwargs)
/usr/share/miniconda/envs/gammapy-dev/lib/python3.7/site-packages/astropy/units/ RuntimeWarning: invalid value encountered in true_divide
  result = super().__array_ufunc__(function, method, *arrays, **kwargs)
/home/runner/work/gammapy-docs/gammapy-docs/gammapy/gammapy/irf/psf/ MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.
  caxes = ax.pcolormesh(energy, offset, containment.value.T, **kwargs)

Theta squared event distribution

As a quick look plot it can be helpful to plot the quadratic offset (theta squared) distribution of the events.

position = SkyCoord(ra=83.63, dec=22.01, unit="deg", frame="icrs")
theta2_axis = MapAxis.from_bounds(0, 0.2, nbin=20, interp="lin", unit="deg2")

observations = data_store.get_observations([23523, 23526])
theta2_table = make_theta_squared_table(
plt.figure(figsize=(10, 5))


  • Find the OBS_ID for the runs of the Crab nebula

  • Compute the expected number of background events in the whole RoI for OBS_ID=23523 in the 1 TeV to 3 TeV energy band, from the background IRF.

Next steps

Now you know how to access and work with H.E.S.S. data. All other tutorials and documentation apply to H.E.S.S. and CTA or any other IACT that provides DL3 data and IRFs in the standard format.