RingBackgroundEstimator¶

class gammapy.background.RingBackgroundEstimator(r_in, width)[source]¶

Bases: object

Ring background method for cartesian coordinates.

Step 1: apply exclusion mask
Step 2: ring-correlate

Parameters:	r_in : `Quantity` Inner ring radius width : `Quantity` Ring width. use_fft_convolution : bool Use FFT convolution?

Examples

Example using RingBackgroundEstimator:

from gammapy.maps import Map
from gammapy.background import RingBackgroundEstimator

filename = '$GAMMAPY_DATA/tests/unbundled/poisson_stats_image/input_all.fits.gz'
images = {
    'counts': Map.read(filename, hdu='counts'),
    'exposure_on': Map.read(filename, hdu='exposure'),
    'exclusion': Map.read(filename, hdu='exclusion'),
}

ring_bkg = RingBackgroundEstimator(r_in='0.35 deg', width='0.3 deg')
results = ring_bkg.run(images)
results['background'].plot()

Attributes Summary

parameters dict of parameters

Methods Summary

`kernel`(image)	Ring kernel.
`run`(images)	Run ring background algorithm.

Attributes Documentation

parameters¶: dict of parameters

Methods Documentation

kernel(image)[source]¶

Ring kernel.

Parameters:	image : `WcsNDMap` Input Map
Returns:	ring : `Ring2DKernel` Ring kernel.

run(images)[source]¶

Run ring background algorithm.

Required Maps: {required}

Parameters:	images : dict of `WcsNDMap` Input sky maps.
Returns:	result : dict of `WcsNDMap` Result sky maps