RingBackgroundEstimator

class gammapy.background.RingBackgroundEstimator(r_in, width)

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?

See also

gammapy.detect.KernelBackgroundEstimator, AdaptiveRingBackgroundEstimator

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

Attributes Documentation

parameters

dict of parameters

Methods Documentation

kernel(self, image)

Ring kernel.

Parameters:

image : WcsNDMap

Input Map

Returns:

ring : Ring2DKernel

Ring kernel.

run(self, images)

Run ring background algorithm.

Required Maps: {required}

Parameters:

images : dict of WcsNDMap

Input sky maps.

Returns:

result : dict of WcsNDMap

Result sky maps