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imager.exprmask - Function

2.5.1 Construct a mask image from a LEL expression


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 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. boxmask does not enforce this requirement.

This function allows Lattice Express Language (LEL) expressions to be used in defining a mask. See the documentation on imagecalc for more details.

Arguments





Inputs

mask

name of mask image

allowed:

string

Default:

expr

Value to set the mask to. Any scalar or LEL expression

allowed:

double

Default:

1.0

Returns
bool

Example

 
 
im.exprmask(mask=’bigmask’, expr=’3C273XC1.clean>0.5’)  
im.clean(mask=’bigmask’, model=’3C273XC1.clean.masked’, niter=1000)  
 
 
Makes the image bigmask, and then sets it to unity for all points in  
the region where 3C273XC1.clean is greater than 0.5Jy.  
Then cleans using it as the mask.  

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