ASmooth

class gammapy.image.ASmooth(kernel=<class 'astropy.convolution.kernels.Gaussian2DKernel'>, method='simple', threshold=5, scales=None)[source]

Bases: object

Adaptively smooth counts image.

Achieves a roughly constant significance of features across the whole image.

Algorithm based on http://adsabs.harvard.edu/abs/2006MNRAS.368...65E

The algorithm was slightly adapted to also allow Li & Ma and TS to estimate the significance of a feature in the image.

Parameters:

kernel : astropy.convolution.Kernel

Smoothing kernel.

method : {‘simple’, ‘asmooth’, ‘lima’}

Significance estimation method.

threshold : float

Significance threshold.

scales : Quantity

Smoothing scales.

Methods Summary

kernels(image) Ring kernels according to the specified method.
run(images) Run image smoothing.

Methods Documentation

kernels(image)[source]

Ring kernels according to the specified method.

Parameters:

image : SkyImage

Sky image specifying the WCS information.
Returns:

kernels : list

List of Kernel
run(images)[source]

Run image smoothing.

Parameters:

images : SkyImageList

List of input sky images.
Returns:

smoothed : SkyImageList

List of smoothed sky images containing:
  • ‘counts’
  • ‘background’
  • ‘flux’ (optional)
  • ‘scales’
  • ‘significance’.