compute_ts_image

gammapy.detect.compute_ts_image(counts, background, exposure, kernel, mask=None, flux=None, method='root brentq', parallel=True, threshold=None)[source]

Compute TS image using different optimization methods.

Parameters:

counts : SkyImage

Counts image.

background : SkyImage

Background image

exposure : SkyImage

Exposure image

kernel : astropy.convolution.Kernel2D or 2D ndarray

Source model kernel.

flux : float (None)

Flux image used as a starting value for the amplitude fit.

method : str (‘root’)

The following options are available:

  • 'root brentq' (default)
    Fit amplitude finding roots of the the derivative of the fit statistics. Described in Appendix A in Stewart (2009).
  • 'root newton'
    TODO: document
  • 'leastsq iter'
    TODO: document

parallel : bool (True)

Whether to use multiple cores for parallel processing.

threshold : float (None)

If the TS value corresponding to the initial flux estimate is not above this threshold, the optimizing step is omitted to save computing time.
Returns:

images : SkyImageList

Images (ts, niter, amplitude)

Notes

Negative \(TS\) values are defined as following:

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

Where \(F\) is the fitted flux amplitude.

References

[Stewart2009]