hogbom_complex

ska_sdp_func_python.image.cleaners.hogbom_complex(dirty_q, dirty_u, psf_q, psf_u, window, gain, thresh, niter, fracthresh)[source]

Clean the point spread function from a dirty Q+iU image.

This uses the complex Hogbom CLEAN for polarised data (2016MNRAS.462.3483P).

The starting-point for the code was the standard Hogbom clean algorithm available in RASCIL.

Parameters:

  • dirty_q – (numpy array): The dirty Q Image, i.e., the Q Image to be deconvolved

  • dirty_u – (numpy array): The dirty U Image, i.e., the U Image to be deconvolved

  • psf_q – (numpy array): The point spread-function in Stokes Q

  • psf_u – (numpy array): The point spread-function in Stokes U

  • window – (float): Regions where clean components are allowed If True, entire dirty Image is allowed

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

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

  • niter – (int): Maximum number of components to make if the threshold thresh is not hit

  • fracthresh – (float): The predefined fractional threshold at which to stop cleaning

Returns:

(comps.real, comps.imag, res.real, res.imag)