ACA Simulation (CASA 3.4): Difference between revisions

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Multiple configurations, or an observation in one 12m configuration plus one ACA observation, or  
Multiple configurations, or an observation in one 12m configuration plus one ACA observation, or  
other combinations, can be simulated by running sim_observe for each, and then combining the  
other combinations, can be simulated by running simobserve for each, and then combining the  
Measurement Sets to run sim_analyze.  Total power observations can be simulated either in an independent run of sim_observe, or along with an interferometric simulation.  Note that if you simulate total power and an interferometric observation simultaneously with sim_observe, they must have the same set of pointing centers and the same integration and total time, which is probably not realistic. (For example it is generally recommended to observe a larger area by 1/2 primary beam in total power mode to combine with a 12m ALMA mosaic).
Measurement Sets to run simanalyze.  Total power observations can be simulated either in an independent run of simobserve, or along with an interferometric simulation.  Note that if you simulate total power and an interferometric observation simultaneously with simobserve, they must have the same set of pointing centers and the same integration and total time, which is probably not realistic. (For example it is generally recommended to observe a larger area by 1/2 primary beam in total power mode to combine with a 12m ALMA mosaic).


=====Set sim_observe as current task=====
=====Set simobserve as current task=====
Reset all parameters to default, and then set the project name to m51c
Reset all parameters to default, and then set the project name to m51c
<source lang="python">
<source lang="python">
# Set sim_observe to default parameters
# Set simobserve to default parameters
default("sim_observe")
default("simobserve")
# Our project name will be m51c, and all simulation products will be placed in a subdirectory m51c/
# Our project name will be m51c, and all simulation products will be placed in a subdirectory m51c/
project="m51c"
project="m51c"
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We'll use an Halpha image of M51 as an example model sky.  Download [[File:M51ha.fits.txt]] and place in your working directory, or use the curl command in the script.
We'll use an Halpha image of M51 as an example model sky.  Download [[File:M51ha.fits.txt]] and place in your working directory, or use the curl command in the script.


sim_observe will make a copy m51c/m51c.skymodel, and not modify your input image.
simobserve will make a copy m51c/m51c.skymodel, and not modify your input image.
<source lang="python">
<source lang="python">
# Model sky = Halpha image of M51  
# Model sky = Halpha image of M51  
Line 47: Line 47:
[[Image:M51c.ALMA_0.5arcsec.skymodel.png|thumb|hexagonal mosaic overplotted on sky model]]
[[Image:M51c.ALMA_0.5arcsec.skymodel.png|thumb|hexagonal mosaic overplotted on sky model]]


We'll begin with the 12m ALMA array observation, and have sim_observe calculate a hexagonal mosaic of pointings.
We'll begin with the 12m ALMA array observation, and have simobserve calculate a hexagonal mosaic of pointings.


The default interface for sim_observe provides an integration parameter, which is the dwell time at each mosaic pointing -- we'll set that to 10s.  A real observation would integrate a scan of ~5 min at each mosaic pointing;  we could set integration="5min" but then for data volume and speed, sim_observe would only generate one measurement per 5min scan.  While thermal noise levels would be scaled correctly, corruption of the data with a phase screen, or the details of uv coverage, would not be realistic.  Rotating through the mosaic more rapidly than a real simulation will result in more representative uv coverage.  If you wish to simulate the more realistic case such as 5 min scans with 5s integrations, please see [[Complex pointingtable]] for a guide to doing that with sim_observe (Its not hard, it just takes two calls to the task instead of one).
The default interface for simobserve provides an integration parameter, which is the dwell time at each mosaic pointing -- we'll set that to 10s.  A real observation would integrate a scan of ~5 min at each mosaic pointing;  we could set integration="5min" but then for data volume and speed, simobserve would only generate one measurement per 5min scan.  While thermal noise levels would be scaled correctly, corruption of the data with a phase screen, or the details of uv coverage, would not be realistic.  Rotating through the mosaic more rapidly than a real simulation will result in more representative uv coverage.  If you wish to simulate the more realistic case such as 5 min scans with 5s integrations, please see [[Complex pointingtable (CASA 3.4)]] for a guide to doing that with simobserve (Its not hard, it just takes two calls to the task instead of one).


<source lang="python">
<source lang="python">
# have sim_observe calculate mosaic pointing locations:
# have simobserve calculate mosaic pointing locations:
setpointings      =  True
setpointings      =  True
integration        =  "10s"
integration        =  "10s"
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=====Calculate Visibilities=====
=====Calculate Visibilities=====
sim_observe can determine what array configuration to use, if you provide a desired resolution or synthesized beam size.   
simobserve can determine what array configuration to use, if you provide a desired resolution or synthesized beam size.   
<source lang="python">
<source lang="python">
observe           =  True
obsmode           =  "int"
antennalist        =  "ALMA;0.5arcsec"
antennalist        =  "ALMA;0.5arcsec"
totaltime          =  "3600s"
totaltime          =  "3600s"
</source>
</source>


run sim_observe, displaying graphics to screen and file (files can be found in the project directory, e.g. m51c)
run simobserve, displaying graphics to screen and file (files can be found in the project directory, e.g. m51c)


<source lang="python">
<source lang="python">
Line 97: Line 97:


<source lang="python">
<source lang="python">
obsmode            = "sd"
sdantlist          = "aca.tp.cfg"
sdantlist          = "aca.tp.cfg"
sdant              = 0
sdant              = 0
refdate            = "2012/12/01"
refdate            = "2012/12/01"
# SET interferometric antennalist to default, or else we'll redo the interferometric simulation too
antennalist        =  ""
totaltime          =  "2h"
totaltime          =  "2h"
</source>
</source>


run sim_observe, displaying graphics to screen and file
run simobserve, displaying graphics to screen and file


<source lang="python">
<source lang="python">
Line 129: Line 128:


<source lang="python">
<source lang="python">
# remember to set this back to empty
obsmode            = "int"
sdantlist          = ""
refdate            = "2012/12/02"
refdate            = "2012/12/02"
antennalist        =  "aca.i.cfg"
antennalist        =  "aca.i.cfg"
Line 136: Line 134:
</source>
</source>


run sim_observe, displaying graphics to screen and file
run simobserve, displaying graphics to screen and file


<source lang="python">
<source lang="python">
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====Deconvolve the visibilities back into an image====
====Deconvolve the visibilities back into an image====


We use sim_analyze to take the three measurement sets and create a single image.  
We use simanalyze to take the three measurement sets and create a single image.  


There are many ways to do this, and the project is NOT making any recommendation yet at this time about what is optimal.  Please discuss with your ARC contact scientist if you have ALMA data now, or wait for additional recommendations to be posted here over time.
There are many ways to do this, and the project is NOT making any recommendation yet at this time about what is optimal.  Please discuss with your ARC contact scientist if you have ALMA data now, or wait for additional recommendations to be posted here over time.
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* An alternative would be to create each image independently, and then use the CASA feather task to combine them entirely in the image plane.
* An alternative would be to create each image independently, and then use the CASA feather task to combine them entirely in the image plane.


sim_analyze, if given a total power and interferometric measurement set, will automatically create the total power image,  
simanalyze, if given a total power and interferometric measurement set, will automatically create the total power image,  
then use it as a model and deconvolve the interferometric image.  It is not recommended to do both interferometric images simultaneously.
then use it as a model and deconvolve the interferometric image.  It is not recommended to do both interferometric images simultaneously.


Line 162: Line 160:


<source lang="python">
<source lang="python">
default("sim_analyze")
default("simanalyze")
project            =  "m51c"
project            =  "m51c"
vis                =  '$project.aca.i.ms,$project.aca.tp.sd.ms'   
vis                =  '$project.aca.i.ms,$project.aca.tp.sd.ms'   
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====Next add the 12m interferometric data====
====Next add the 12m interferometric data====
[[Image:M51c.ALMA_0.5arcsec.analysis.png|thumb|TP+ACA combined (with relatively low weight) with 12m ALMA]]
[[Image:M51c.ALMA_0.5arcsec.analysis.3.4.png|thumb|TP+ACA combined (with relatively low weight) with 12m ALMA]]
Here we explicitly have to set the modelimage to the previous output.
Here we explicitly have to set the modelimage to the previous output.


<source lang="python">
<source lang="python">
default("sim_analyze")
default("simanalyze")
project            =  "m51c"
project            =  "m51c"
vis                =  '$project.ALMA_0.5arcsec.ms'
vis                =  '$project.ALMA_0.5arcsec.ms'

Latest revision as of 10:37, 8 June 2012

Simulating Observations in CASA

To create a script of the Python code on this page see Extracting scripts from these tutorials.

ALMA 12m + ACA + Total Power

Multiple configurations, or an observation in one 12m configuration plus one ACA observation, or other combinations, can be simulated by running simobserve for each, and then combining the Measurement Sets to run simanalyze. Total power observations can be simulated either in an independent run of simobserve, or along with an interferometric simulation. Note that if you simulate total power and an interferometric observation simultaneously with simobserve, they must have the same set of pointing centers and the same integration and total time, which is probably not realistic. (For example it is generally recommended to observe a larger area by 1/2 primary beam in total power mode to combine with a 12m ALMA mosaic).

Set simobserve as current task

Reset all parameters to default, and then set the project name to m51c

# Set simobserve to default parameters
default("simobserve")
# Our project name will be m51c, and all simulation products will be placed in a subdirectory m51c/
project="m51c"
Specify sky model image

We'll use an Halpha image of M51 as an example model sky. Download File:M51ha.fits.txt and place in your working directory, or use the curl command in the script.

simobserve will make a copy m51c/m51c.skymodel, and not modify your input image.

# Model sky = Halpha image of M51 
os.system('curl http://casaguides.nrao.edu/images/3/3f/M51ha.fits.txt -f -o M51ha.fits.txt')
skymodel         =  "M51ha.fits.txt"

Although the image has a world coordinate system, we want to override most of the parameters.

  • We'll place the source in the southern hemisphere with the indirection parameter,
  • set the pixel size to 0.1arcsec, effectively moving the galaxy further away (M51 itself would require a quite large mosaic, and in any case we need for the input model pixels to be significantly smaller than the synthesized beam that we'll be simulating, or else we won't be learning anything)
  • consistent with simulating a more distant source, we'll set the peak brightness to 0.004 Jy/pixel
  • set the frequency to 330GHz, and since its a 2D image we'll set the single "channel" width to be 50MHz, and peak brightness of 0.004 Jy/pixel - parameters plausible for observing an emission line in a galaxy.
# Set model image parameters:
indirection="B1950 23h59m59.96s -34d59m59.50s"
incell="0.1arcsec"
inbright="0.004"
incenter="330.076GHz"
inwidth="50MHz"



Simulate 12m interferometric observation

hexagonal mosaic overplotted on sky model

We'll begin with the 12m ALMA array observation, and have simobserve calculate a hexagonal mosaic of pointings.

The default interface for simobserve provides an integration parameter, which is the dwell time at each mosaic pointing -- we'll set that to 10s. A real observation would integrate a scan of ~5 min at each mosaic pointing; we could set integration="5min" but then for data volume and speed, simobserve would only generate one measurement per 5min scan. While thermal noise levels would be scaled correctly, corruption of the data with a phase screen, or the details of uv coverage, would not be realistic. Rotating through the mosaic more rapidly than a real simulation will result in more representative uv coverage. If you wish to simulate the more realistic case such as 5 min scans with 5s integrations, please see Complex pointingtable (CASA 3.4) for a guide to doing that with simobserve (Its not hard, it just takes two calls to the task instead of one).

# have simobserve calculate mosaic pointing locations:
setpointings       =  True
integration        =  "10s"
mapsize            =  "1arcmin"
maptype            =  "hex"
pointingspacing    =  "9arcsec"      # this could also be specified in units of the primary beam e.g. "0.5PB"
Calculate Visibilities

simobserve can determine what array configuration to use, if you provide a desired resolution or synthesized beam size.

obsmode            =  "int"
antennalist        =  "ALMA;0.5arcsec"
totaltime          =  "3600s"

run simobserve, displaying graphics to screen and file (files can be found in the project directory, e.g. m51c)

graphics           =  "both"
go



Simulate 12m total power observation

rectangular map overplotted on sky model

Next we'll simulate a total power raster map of the same area, but on a more realistic square grid. CASA simulation tools can not simulate true on-the-fly mapping (with smearing on timescales smaller than an integration time), but a square grid with a short integration time will provide a very accurate approximation.

By virtue of CASA's global parameters, we already have project and image world coordinate system parameters set correctly.

We need to change the pointing calculation to make it square and a bit larger than the interferometric map.

integration        =  "10s"
mapsize            =  "1.3arcmin"
maptype            =  "square"

We'll observe on a different day (this doesn't really matter, but if you choose to simulate two different 12m ALMA configurations and combine them, if they're simulated on the same day with the same antenna names you will have issues concatenating the datasets, so its a good habit to change the day)

obsmode            = "sd"
sdantlist          = "aca.tp.cfg"
sdant              = 0
refdate            = "2012/12/01"
totaltime          =  "2h"

run simobserve, displaying graphics to screen and file

go



Simulate 7m ACA observation

hexagonal map overplotted on sky model

Next we'll add an ACA mosaic, with its larger primary beam.

integration        =  "10s"
mapsize            =  "1arcmin"
maptype            =  "hex"
pointingspacing    =  "15arcsec"

We can specify an integral number of times to repeat the mosaic by setting totaltime to an integer string without units.

obsmode            = "int"
refdate            = "2012/12/02"
antennalist        =  "aca.i.cfg"
totaltime          =  "3"

run simobserve, displaying graphics to screen and file

go



Deconvolve the visibilities back into an image

We use simanalyze to take the three measurement sets and create a single image.

There are many ways to do this, and the project is NOT making any recommendation yet at this time about what is optimal. Please discuss with your ARC contact scientist if you have ALMA data now, or wait for additional recommendations to be posted here over time.

  • We will use the total power image as a model when deconvolving the ACA image, and then use the result as a model when deconvolving the 12m interferometric image. This tends to give low weight to the large spatial scales, but is simple to illustrate.
  • Improved results would result if one used multiscale clean, in the clean task (again using the lower resolution image as a model when deconvolving the higher resolution one)
  • An alternative would be to create each image independently, and then use the CASA feather task to combine them entirely in the image plane.

simanalyze, if given a total power and interferometric measurement set, will automatically create the total power image, then use it as a model and deconvolve the interferometric image. It is not recommended to do both interferometric images simultaneously.

First image total power and ACA with total power as a model

Total power combined (with relatively low weight) with ACA
default("simanalyze")
project            =  "m51c"
vis                =  '$project.aca.i.ms,$project.aca.tp.sd.ms'  
imsize             =  [512,512]
cell               =  '0.2arcsec'
analyze            =  True
showpsf            =  False
showresidual       =  False
showconvolved      =  True
go()



Next add the 12m interferometric data

TP+ACA combined (with relatively low weight) with 12m ALMA

Here we explicitly have to set the modelimage to the previous output.

default("simanalyze")
project            =  "m51c"
vis                =  '$project.ALMA_0.5arcsec.ms'
imsize             =  [512,512]
cell               =  '0.1arcsec'
modelimage         =  "$project.aca.i.image"
analyze            =  True
showpsf            =  False
showresidual       =  False
showconvolved      =  True
go()


Simulating Observations in CASA