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Module | imager | |
Tool | imager |
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.
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.
Construct a mask image from a LEL expression
Synopsis
exprmask(mask, expr)
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.
Arguments
mask
name of mask image
Allowed:
String
expr
Value to set the mask to
Allowed:
Any scalar or LEL expression
Default:
1.0
Returns
Bool
Example
imgr.exprmask(mask='bigmask', expr='"3C273XC1.clean">0.5')
imgr.clean(mask='bigmask', model='3C273XC1.clean.masked', niter=1000)
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2006-10-15