ska_sdp_spectral_line_imaging.data_procs.deconvolution.deconvolver module
- ska_sdp_spectral_line_imaging.data_procs.deconvolution.deconvolver.deconvolve_cube(dirty, psf, **kwargs)[source]
Note: This documentation copied from ska_sdp_func_python.image.deconvolution.deconvolve_cube. Not all parameters and algorithms are currently supported.
Clean using a variety of algorithms.
The algorithms available are:
hogbom: Hogbom CLEAN See: Hogbom CLEAN A&A Suppl, 15, 417, (1974)
hogbom-complex: Complex Hogbom CLEAN of stokesIQUV image
msclean: MultiScale CLEAN See: Cornwell, T.J., Multiscale CLEAN (IEEE Journal of Selected Topics in Sig Proc, 2008 vol. 2 pp. 793-801)
mfsmsclean, msmfsclean, mmclean: MultiScale Multi-Frequency See: U. Rau and T. J. Cornwell, “A multi-scale multi-frequency deconvolution algorithm for synthesis imaging in radio interferometry,” A&A 532, A71 (2011).
For example:
comp, residual = deconvolve_cube(dirty, psf, niter=1000, gain=0.7, algorithm='msclean', scales=[0, 3, 10, 30], threshold=0.01)
For the MFS clean, the psf must have number of channels >= 2 * nmoment.
- Parameters:
dirty (
Image) -- Image dirty imagepsf (
Image) -- Image Point Spread Functionsensitivity -- Sensitivity image (i.e. inverse noise level)
prefix -- Informational message for logging
window_shape -- Window description
mask -- Window in the form of an image, overrides window_shape
algorithm -- Cleaning algorithm: 'msclean'|'hogbom'
gain -- loop gain (float) 0.7
threshold -- Clean threshold (0.0)
fractional_threshold -- Fractional threshold (0.01)
scales -- Scales (in pixels) for multiscale ([0, 3, 10, 30])
nmoment -- Number of frequency moments (default 3)
findpeak -- Method of finding peak in mfsclean: 'Algorithm1'|'ASKAPSoft'|'CASA'|'RASCIL', Default is RASCIL.
- Return type:
- Returns:
component image, residual image
- See also
ska_sdp_func_python.image.cleaners.hogbom()ska_sdp_func_python.image.cleaners.hogbom_complex()ska_sdp_func_python.image.cleaners.msclean()ska_sdp_func_python.image.cleaners.msmfsclean()