hogbom_complex

hogbom_complex(dirty_q, dirty_u, psf_q, psf_u, window, gain, thresh, niter, fracthresh)

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 ARL.

Args: 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: real clean component image. comps.imag: imaginary clean component image. res.real: real residual image. res.imag: imaginary residual image.