deconvolve Namespace Reference

Functions
def	deconvolve

---

Function Documentation

def deconvolve.deconvolve	(		imagename = '',
			model = '',
			psf = [''],
			alg = 'clark',
			niter = 10,
			gain = 0.1,
			threshold = '0.0mJy',
			mask = '',
			scales = [0,
			sigma = '0.0mJy',
			targetflux = '1.0Jy',
			prior = ''
	)

Image based deconvolver

Several algorithms are available to deconvolve an image with a
known psf (dirty beam), or a Gaussian beam.  The algorithms
available are clark and hogbom clean, a multiscale clean and a
mem clean.  For more deconvolution control, use clean.

Keyword arguments:
imagename -- Name of input image to be deconvolved
model     -- Name of output image containing the clean components
psf       -- Name of psf image (dirty beam) to use
             example: psf='casaxmlf.image' .
             If the psf has 3 parameter, then a Gaussian
             psf is assumed with the values representing
             the major , minor and position angle  values
             e.g  psf=['3arcsec', '2.5arcsec', '10deg']
alg       -- algorithm to use: default = 'clark'
               options: clark, hogbom, multiscale or mem.
niter     -- Maximum number of iterations
gain      -- CLEAN gain parameter; fraction to remove from peak
threshold -- Halt deconvolution if the maximum residual image is
             below this threshold.
             default = '0.0Jy'
mask      -- mask image (same shape as image and psf) to limit region
             where deconvoltion is to occur

------parameters useful for multiscale only
scales     -- in pixel numbers; the size of component to deconvolve.
              default value [0,3,10]
              recommended sizes are 0 (point), 3 (points per clean beam), and
              10 (about a factor of three lower resolution)
------parameters useful for mem only
sigma      -- Estimated noise for image
targetflux -- Target total flux in image 
prior      -- Prior image to guide mem

Definition at line 13 of file deconvolve.py.

References task_deconvolve.deconvolve(), publish_summary.quantity, and vla_uvfits_line_sf.verify.