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imager.makemodelfromsd - Function

	Package	synthesis
	Module	imager
	Tool	imager

Make stating model image from a Single Dish image

Synopsis
makemodelfromsd(sdimage, modelimage, sdpsf, maskimage)

Description
This functions use an image from a single dish and make a model (clean component) image out of it. This allows one to use this as the starting model in a deconvoltion function e.g clean or mem This provides an alternative to feather. The difference between the two is that in feather the interferometer image is deconvolved first and the single dish image is put in at the end. Whereas if one starts with a model from the single dish image it will give a different starting point for the deconvolving algorithm to interpolate the missing short baseline.

The function setsdoptions to set a factor by which to scale the SD image, if necessary.

The sdpsf parameter (optional) should be used if an external PSF image of the single dish is needed to calculate the beam parameters of the primary beam of the dish. This is usually needed if the dish image is from a non standard telescope or the beam is not in the aips++ system. This parameter should point to an image, if you have a vptable made from vpmanager then setvp should be used to define this beam.

The mask is a mask image that may be needed to be used for clean. This is usually the case when the dish image does not fully cover the field defined by setimage.

Arguments

sdimage	in	Single Dish image
		Allowed:	String
		Default:	''
modelimage	in	Name of output image to be used as model
		Allowed:	String
		Default:	''
sdpsf	in	PSF of Single Dish if needed
		Allowed:	String
		Default:	''
maskimage	in	mask image
		Allowed:	String
		Default:	''

Returns
Bool

Example

myim:=imager('orion\_only.ms')
myim.setdata(fieldid=[1:10], spwid=[1:2])
myim.setimage(nx=1000, ny=1000, cellx='1arcsec', celly='1arcsec', fieldid=5, spwid=[1,2])
myim.setvp(dovp=T)
myim.setoptions(ftmachine='mosaic')
myim.setscales(nscales=3)
myim.setsdoptions(scale=0.9);
myim.makemodelfromsd(sdimage='orion\_gbt.im', modelimage='orion\_model', maskimage='orion.mask')
myim.clean(algorithm='mfmultiscale', model='orion\_model',
residual='orion.residual', image='orion.restored', gain=0.2, niter=500, mask='orion.mask')

In the above example we are making a mosaic with the fields 1 to 10. A single dish image orion_gbt.im is used scaled down by a factor 0.9 to make the initial model that is passed to multi-scale clean.