simanalyze – image and analyze measurement sets created with simobserve – simulation task

Description

This task is for imaging and analyzing measurement sets (MSs) simulated
with simobserve or simalma.

Parameters

Title
Parameter	Default	Description
project	`'sim'`	root prefix for output file names
image	`True`
imagename	`'default'`
skymodel	`''`
vis	`'default'`
modelimage	`''`
imsize	`numpy.array( [ int(0),int(0) ] )`
imdirection	`''`
cell	`''`
interactive	`False`
niter	`int(0)`
threshold	`'0.1mJy'`
weighting	`'natural'`
mask	`numpy.array( [ ] )`
outertaper	`numpy.array( [ ] )`
pbcor	`True`
stokes	`'I'`
featherimage	`''`
analyze	`False`
showuv	`True`
showpsf	`True`
showmodel	`True`
showconvolved	`False`
showclean	`True`
showresidual	`False`
showdifference	`True`
showfidelity	`True`
graphics	`'both'`
verbose	`False`
overwrite	`True`
dryrun	`False`
logfile	`''`

Parameter Explanations

project

'sim'

root prefix for input and output file names. This must be the directory of results generated by running simobserve or simalma. In particular $project/$project.skymodel will be required in order to compare output and input images.

image

True

(re)image $project.*.ms to $project.image

imagename

'default'

simulation output image to analyze (default = first $project/*.image found)

skymodel

''

skymodel image to analyze (the .skymodel image created by simobserve or simalma and used by one of those tasks to create an MS; if unspecified, will try to find one similar to your specified output image name)

vis

'default'

Measurement Set(s) to image

modelimage

''

lower resolution prior image to use in clean e.g. existing total power image

imsize

numpy.array( [ int(0),int(0) ] )

output image size in pixels (x,y) or 0 to match model

imdirection

''

set output image direction, (otherwise center on the model)

cell

''

cell size with units e.g. “10arcsec” or “” to equal model

interactive

False

interactive clean? (make sure to set niter>0 also)

niter

int(0)

maximum number of iterations (0 for dirty image)

threshold

'0.1mJy'

flux level (+units) to stop cleaning

weighting

'natural'

weighting to apply to visibilities. briggs will use robust=0.5

mask

numpy.array( [ ] )

Cleanbox(es), mask image(s), region(s), or a level

outertaper

numpy.array( [ ] )

uv-taper on outer baselines in uv-plane

pbcor

True

correct the output of synthesis images for primary beam response?

stokes

'I'

Stokes params to image

featherimage

''

image (e.g. total power) to feather with new image

analyze

False

(only first 6 selected outputs will be displayed)

showuv

True

display uv coverage

showpsf

True

display synthesized (dirty) beam (ignored in single dish simulation)

showmodel

True

display sky model at original resolution

showconvolved

False

display sky model convolved with output clean beam

showclean

True

display the synthesized image

showresidual

False

display the clean residual image (ignored in single dish simulation)

showdifference

True

display difference between output cleaned image and input model sky image convolved with output clean beam

showfidelity

True

display fidelity (see help)

graphics

'both'

display graphics at each stage to [screen|file|both|none]

verbose

False

overwrite

True

overwrite files starting with $project

dryrun

False

only print information [experimental; only for interfermetric data]

logfile

''