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imager.mask - Function

2.3.1 Construct a mask image by thresholding an image


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. One makes a mask image by clipping the I part of the restored image (this function) or via the boxmask, regionmask, and exprmask functions. In this function, all points greater than the threshold are set to unity. The mask is the same in I,Q,U, and V. Note that exprmask is the most powerful method for making mask images.

In the Clark CLEAN, the mask image can usefully have any value between 0.0 and 1.0. Intermediate value discourage 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. It is particularly important to check this when creating an image using a threshold. If it extends further, the easiest fix is to use getchunk and getchunk to set parts of it to zero.

Arguments





Inputs

image

name of template image

allowed:

string

Default:

mask

name of mask image

allowed:

string

Default:

threshold

threshold for mask

allowed:

any

Default:

variant 0.0Jy

async

Run asynchronously in the background

allowed:

bool

Default:

false

Returns
bool

Example

 
 
im.mask( image=’bigimage’, mask=’bigmask’,threshold=’0.07Jy’)  
im.clean(mask=’bigmask’, model=’3C273XC1.clean.masked’, niter=1000)  
 
 
Makes the image bigmask, and then sets it to unity  
for all points where the Stokes I in bigimage is  
greater than 0.07. Then clean using it as the mask.  

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