BackgroundModel

class gammapy.cube.models.BackgroundModel(background, norm=1, tilt=0, reference='1 TeV')

Bases: gammapy.utils.fitting.Model

Background model.

Create a new map by a tilt and normalisation on the available map

Parameters:

background : Map

Background model map

norm : float

Background normalisation

tilt : float

Additional tilt in the spectrum

reference : Quantity

Reference energy of the tilt.

Attributes Summary

energy_center	True energy axis bin centers (Quantity)
map
norm
parameters	Parameters (Parameters)
reference
tilt

Methods Summary

copy()	A deep copy.
evaluate()	Evaluate background model.
from_skymodel(skymodel, exposure[, edisp, psf])	Create background model from sky model by applying IRFs.

Attributes Documentation

energy_center

True energy axis bin centers (Quantity)

map

norm

parameters

Parameters (Parameters)

reference

tilt

Methods Documentation

copy()

A deep copy.

evaluate()

Evaluate background model.

Returns:

background_map : Map

Background evaluated on the Map

classmethod from_skymodel(skymodel, exposure, edisp=None, psf=None, **kwargs)

Create background model from sky model by applying IRFs.

Typically used for diffuse Galactic or constant emission models.

Parameters:

skymodel : SkyModel or SkyDiffuseCube

Sky model

exposure : Map

Exposure map

edisp : EnergyDispersion

Energy dispersion

psf : PSFKernel

PSF kernel