3.1.2.0 deconvolver.regionmask

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deconvolver.regionmask - Function

3.1.2 Construct a mask image from a region

Description

A mask image is an image with the same shape as the other images but with values between 0.0 and 1.0 as a pixel value. Mask images are used in imager to control the region selected in a deconvolution.

In Clark CLEAN, the mask image can usefully have any value between 0.0 and 1.0. Intermediate value is discouraged but do not rule out selection of clean components in that region. This is accomplished by multiplying the residual image by the mask prior to entering the minor cycle. Note that if you do use a mask for the Clark or Hogbom Clean, it must cover only a quarter of the image. regionmask does not enforce this requirement.

The function regionmask also allows multiple regions to be used. A record of the regions can be made as in the example below.

Regions can be made in many different ways using the regionmanager functions. An example using wbox function is given below. The default regionmanager tool ’rg’ can be used for cases the user want to have flexibility in manipulating regions. The region parameter takes a record that comes from the regionmanager output. The parameter boxes allow the user to sent in a list of 4 elements numbers representing blc’s and trc’s

If both the parameters, regions and boxes are used the a union is done with the two sets of region thus defined.

Arguments


Inputs
mask	name of mask image
	allowed:	string
	Default:
region	Region record usually from regionmanager
	allowed:	record
	Default:	unset
boxes	list of 4 elements lists e.g [[xblc1, yblc1, xtrc1, ytrc1], [[xblc2, yblc2, xtrc2, ytrc2]]
	allowed:	any
	Default:	variant
value	Value to set the mask to
	allowed:	double
	Default:	1.0

Returns
bool

Example

Makes a mask then cleans using it.

dc.open(dirty.image’, ’psf.image’)
a=[100.0, 100.0, 200, 200.0]
b=[50, 50, 80, 80]
dc.regionmask(mask=’bigmask’, boxes[a,b])
dc.clean(algorithm=’hogbom’, mask=’bigmask’, model=’model.clean.masked’, niter=1000)

Another example using rg.wbox function:
ia.open(’dirty’)
cs:=ia.coordsys()
rg.setcoordinates(cs.record())
r1:=dg.wbox(blc=[’173pix’, ’347pix’], trc=[’183pix’, ’370pix’])
c.regionmask(mask=’bigmask’,region=r1)

Or using a dict of regions:

r2=rg.wbox(blc=[’180pix’, ’344pix’], trc=[’191pix’, ’369pix’])
r3=rg.wbox(blc=[’189pix’, ’341pix’], trc=[’204pix’, ’364pix’])
regs={"reg1"’:r1, "reg2":r2, "reg3":r3}
rec=rg.makeunion(regs)
dc.regionmask(mask=’bigmask’,region=rec)

If quantities are to be used to define regions the following is a an example

dc.regionmask(mask=’joetest’,boxes=[’15:23:32.902’,’+05.19.32.089’,’15:22:28.631’,’+05.28.52.474’])

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