AdaptiveRingBackgroundMaker

class gammapy.cube.AdaptiveRingBackgroundMaker(r_in, r_out_max, width, stepsize='0.02 deg', threshold_alpha=0.1, theta='0.22 deg', method='fixed_width', exclusion_mask=None)

Bases: object

Adaptive ring background algorithm.

This algorithm extends the RingBackgroundMaker method by adapting the size of the ring to achieve a minimum on / off exposure ratio (alpha) in regions where the area to estimate the background from is limited.

Parameters

r_inQuantity

Inner radius of the ring.

r_out_maxQuantity

Maximal outer radius of the ring.

widthQuantity

Width of the ring.

stepsizeQuantity

Stepsize used for increasing the radius.

threshold_alphafloat

Threshold on alpha above which the adaptive ring takes action.

thetaQuantity

Integration radius used for alpha computation.

method{‘fixed_width’, ‘fixed_r_in’}

Adaptive ring method.

exclusion_maskWcsNDMap

Exclusion mask

See also

RingBackgroundMaker, gammapy.detect.KernelBackgroundEstimator

Methods Summary

kernels(self, image)	Ring kernels according to the specified method.
make_cubes(self, dataset)	Make acceptance, off acceptance, off counts cubes
run(self, dataset)	Run adaptive ring background maker

Methods Documentation

kernels(self, image)

Ring kernels according to the specified method.

Parameters

imageWcsNDMap

Map specifying the WCS information.

Returns

kernelslist

List of Ring2DKernel

make_cubes(self, dataset)

Make acceptance, off acceptance, off counts cubes

Parameters

datasetMapDataset

Input map dataset.

Returns

cubesdict of WcsNDMap

Dictionary containing counts_off, acceptance and acceptance_off cubes.

run(self, dataset)

Run adaptive ring background maker

Parameters

datasetMapDataset

Input map dataset.

Returns

dataset_on_offMapDatasetOnOff

On off dataset.