ASmoothMapEstimator

class gammapy.estimators.ASmoothMapEstimator(scales=None, kernel=<class 'astropy.convolution.kernels.Gaussian2DKernel'>, spectrum=None, method='lima', threshold=5, energy_edges=None)

Bases: gammapy.estimators.Estimator

Adaptively smooth counts image.

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

Algorithm based on https://ui.adsabs.harvard.edu/abs/2006MNRAS.368…65E

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

Parameters

scalesQuantity

Smoothing scales.

kernelastropy.convolution.Kernel

Smoothing kernel.

spectrumSpectralModel

Spectral model assumption

method{‘asmooth’, ‘lima’}

Significance estimation method.

thresholdfloat

Significance threshold.

Attributes Summary

config_parameters	Config parameters
selection_optional
tag

Methods Summary

copy()	Copy estimator
estimate_maps(dataset)	Run adaptive smoothing on input Maps.
get_kernels(pixel_scale)	Get kernels according to the specified method.
get_scales(n_scales[, factor, kernel])	Create list of Gaussian widths.
get_sqrt_ts(ts, norm)	Compute sqrt(TS) value.
run(dataset)	Run adaptive smoothing on input MapDataset.
selection_all()	Which quantities are computed

Attributes Documentation

config_parameters

Config parameters

selection_optional

tag = 'ASmoothMapEstimator'

Methods Documentation

copy()

Copy estimator

estimate_maps(dataset)

Run adaptive smoothing on input Maps.

Parameters

datasetMapDataset

Dataset

Returns

imagesdict of WcsNDMap

Smoothed images; keys are:

• ‘counts’

• ‘background’

• ‘flux’ (optional)

• ‘scales’

• ‘sqrt_ts’.

get_kernels(pixel_scale)

Get kernels according to the specified method.

Parameters

pixel_scaleAngle

Sky image pixel scale

Returns

kernelslist

List of Kernel

static get_scales(n_scales, factor=1.4142135623730951, kernel=<class 'astropy.convolution.kernels.Gaussian2DKernel'>)

Create list of Gaussian widths.

Parameters

n_scalesint

Number of scales

factorfloat

Incremental factor

Returns

scalesndarray

Scale array

static get_sqrt_ts(ts, norm)

Compute sqrt(TS) value.

Compute sqrt(TS) as defined by:

\[\begin{split}\sqrt{TS} = \left \{ \begin{array}{ll} -\sqrt{TS} & : \text{if} \ norm < 0 \\ \sqrt{TS} & : \text{else} \end{array} \right.\end{split}\]

Parameters

tsndarray

TS value.

normndarray

norm value

Returns

——-

sqrt_tsndarray

Sqrt(TS) value.

run(dataset)

Run adaptive smoothing on input MapDataset.

Parameters

datasetMapDataset or MapDatasetOnOff

the input dataset (with one bin in energy at most)

Returns

imagesdict of WcsNDMap

Smoothed images; keys are:

• ‘counts’

• ‘background’

• ‘flux’ (optional)

• ‘scales’

• ‘sqrt_ts’.

selection_all()

Which quantities are computed