msmfsclean

ska_sdp_func_python.image.cleaners.msmfsclean(dirty, psf, window, sensitivity, gain, thresh, niter, scales, fracthresh, findpeak='RASCIL', prefix='')[source]

Perform image plane multiscale multi frequency clean.

This algorithm is documented as Algorithm 1 in: U. Rau and T. J. Cornwell, “A multi-scale multi-frequency deconvolution algorithm for synthesis imaging in radio interferometry,” A&A 532, A71 (2011). Note that this is only the image plane parts.

Specific code is linked to specific lines in that algorithm description.

This version operates on numpy arrays that have been converted to moments on the last axis.

Parameters:

  • dirty – The dirty image, i.e., the image to be deconvolved

  • psf – The point spread-function

  • window – Regions where clean components are allowed. If True, all of the dirty image is allowed

  • sensitivity – Inverse noise image, scaled to peak 1.0

  • gain – The “loop gain”, i.e., the fraction of the brightest pixel that is removed in each iteration

  • thresh – Cleaning stops when the maximum of the absolute deviation of the residual is less than this value

  • niter – Maximum number of components to make if the threshold “thresh” is not hit

  • scales – Scales (in pixels width) to be used

  • fracthresh – Fractional stopping threshold

  • findpeak – Method of finding peak in mfsclean: ‘Algorithm1’|’CASA’|’RASCIL’, Default is RASCIL.

  • prefix – Prefix to log messages to provide context

Returns:

clean component image, residual image