make_bg_cube_models

gammapy.scripts.make_bg_cube_models(indir, outdir, overwrite=False, test=False, method='default')

Create background cube models from the complete dataset of an experiment.

Starting with gamma-ray event lists and effective area IRFs, make background templates. Steps

1. make a global event list from a datastore
2. filter the runs keeping only the ones far from known sources

3. group the runs according to similar observation conditions (i.e. alt, az)

   • using ObservationGroups

4. create a bg cube model for each group using:

   • the make_bg_cube_model method
   • and FOVCubeBackgroundModel objects as containers

The models are stored into FITS files.

It can take a few minutes to run. For a quicker test, please activate the test flag.

Parameters:

indir : str

Input directory (that contains the event lists)

outdir : str

Dir path to store the results.

overwrite : bool

If true, run fast (not recommended for analysis).

test : bool

If true, run fast (not recommended for analysis).

method : {‘default’, ‘michi’}

Bg cube model calculation method to apply.

Examples

$ gammapy-make-bg-cube-models -h $ gammapy-make-bg-cube-models <indir> HESS bg_cube_models $ gammapy-make-bg-cube-models <indir> HESS bg_cube_models –test $ gammapy-make-bg-cube-models <indir> HESS bg_cube_models –test –overwrite $ gammapy-make-bg-cube-models <indir> HESS bg_cube_models –method michi