Description
Calculate the approximate point spread function.
Note that the model visibilities are updated.
Some types of imaging do not yield a well-defined point spread
function. For example, mosaicing or single dish imaging both yield
point spread functions that are position dependent. Nevertheless, one
can still usefully define an approximate PSF that is of some
utility. This is calculated by doing the following calculation: a
point source is located at the center of the specified coordinate
system and the model data predicted. The approximate PSF is then formed from
those model data using the full sky equation. For regular sampling in
the image plane, this approximate PSF is actually quite good. It can
be used in a deconvolution. For a mosaic with similar uv sampling per
pointing, the approximate PSF is roughly the PSF per pointing
multiplied by the primary beam. For a single dish image, it is roughly
the telescope primary beam convolved with itself (if the
gridfunction='pb' was selected).
Arguments
| model |
|
Names of input models |
|
|
Allowed: |
Vector of Strings |
| psf |
|
Names of output point spread functions |
|
|
Allowed: |
Vector of Strings |
| async |
|
Run asynchronously in the background |
|
|
Allowed: |
Bool |
|
|
Default: |
!dowait |
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