Protoplanetary Disk Simulation (CASA 3.4): Difference between revisions

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{{Simulations Intro}}
[[Category: Simulations]]
 
* '''This is an advanced simulation tutorial.  New users are recommended to begin with the [[Simulation Guide for New Users (CASA 3.4)]].'''
* '''This guide is applicable to CASA version 3.4.  For older versions of CASA see [[PPdisk_simdata_(CASA_3.3)]].'''
* '''To create a script of the Python code on this page see [[Extracting scripts from these tutorials]].'''
 
== Data ==
 
For this CASA Guide we will use [ftp://ftp.cv.nrao.edu/NRAO-staff/rindebet/input50pc_672GHz.fits a protoplanetary disk model] from S. Wolf.  ''If you use this FITS data for anything more than learning CASA, please cite [http://adsabs.harvard.edu/abs/2005ApJ...619.1114W Wolf & D'Angelo 2005].''
 
== Script with Explanation ==
 
Set '''simobserve''' as the current task and reset all parameters.
 
<source lang="python">
# In CASA
default("simobserve")
</source>
 
Review the image coordinate system using task {{imhead}}.
 
<source lang="python">
# This reports image header parameters in the Log Messages window
imhead("input50pc_672GHz.fits")
</source> 
 
We now use the '''ia''' (image analysis) and '''qa''' (units and quantities) tools from the CASA Toolkit to find the image center.  In comparison to tasks, tools are a more advanced way of manipulating data in CASA.  You can learn more about tools using the [http://casa.nrao.edu/docs/CasaRef/CasaRef.html tool reference manual].
 
When data are being manipulated with tools the data file must be explicitly opened and closed.
 
<source lang="python">
# In CASA
ia.open("input50pc_672GHz.fits")
</source>
 
Next, get the right ascension and declination of the image center.  We get the number of pixels along each axis using '''ia.shape'''.  Then, we get the RA and Dec values for the center pixel using '''ia.toworld'''.
 
<source lang="python">
# In CASA
axesLength = ia.shape()
# Divide the first two elements of axesLength by 2.
center_pixel = [ x / 2.0 for x in axesLength[:2] ]
# Feed center_pixel to ia.toworld and and save the RA and Dec to ra_radians and dec_radians
(ra_radians, dec_radians) = ia.toworld( center_pixel )['numeric'][:2]
ia.close()
</source>
 
Use the '''qa''' tool to convert the image center from radians to sexagesimal coordinates.
 
<source lang="python">
ra_hms  = qa.formxxx(str(ra_radians)+"rad",format='hms',prec=5)
dec_dms = qa.formxxx(str(dec_radians)+"rad",format='dms',prec=5)
</source>
 
Let's call our project "psim2".  This defines the root prefix for any output files from simobserve.
<source lang="python">
project = "psim2"
</source>
 
We'll set '''skymodel''' to the FITS file downloaded, above, and leave all '''skymodel''' subparameters at their default values.  simobserve will create CASA image <tt>psim2.skymodel</tt>.
<source lang="python">
skymodel = "input50pc_672GHz.fits"
</source> 
We will specify the sky position for the center of the observation and set the map size to the size of the model image.  Since the model image is 2/3 arcseconds across, we should only need one pointing.  In this case, '''pointingspacing''' and '''maptype''' can be left at their default values.
 
<source lang="python">
setpointings      =  True
direction          =  "J2000 18h00m00.031s -22d59m59.6s"
mapsize            =  "0.76arcsec"
</source>
 
We do want to simulate an interferometric observation, so we set '''obsmode''' accordingly.  We'll set '''totaltime''' to a 20-minute snapshot observation.
 
<source lang="python">
obsmode            =  "int"
totaltime          =  "1200s"
</source>
 
We want to use the appropriate antenna configuration for the desired angular resolution.  Configuration 20, <tt>alma.out20.cfg</tt>, is the largest "compact" configuration.
 
<source lang="python">
antennalist        =  "alma.out20.cfg"
</source>
 
Now run simobserve.
 
<source lang="python">
simobserve()
</source>
 
Now that we've simulated the visibility measurements, we want to generate an image from the simulated data.  '''simanalyze''' makes this easy.  We begin by setting '''project''' to the same prefix used in simobserve and setting '''image''' to True.
 
<source lang="python">
default ("simanalyze")
project = "psim2"
image = True
</source>
 
We set '''modelimage''' to use the input FITS image when cleaning the simulated visibilities.  We set the image size to 192 pixels square.
 
<source lang="python">
modelimage = "input50pc_672GHz.fits"
vis = project + ".alma.out20.ms"
imsize = [192, 192] 
</source>
 
Specify the number of iterations for cleaning, with proper threshold and weighting.
 
<source lang="python">
niter = 10000
threshold = "1e-7Jy"
weighting = "natural"   
</source>
 
We'd like to calculate a difference and fidelity image, but we don't need to see the uv coverage.
 
<source lang="python">
analyze = True 
showuv = False
showresidual = True 
showconvolved = True
</source>
 
Plot both to the screen and PNG files with lots of messages.
 
<source lang="python">
graphics = "both"
verbose = True
overwrite = True
</source>
 
Run simanalyze.
 
<source lang="python">
simanalyze()
</source>
 
==Simulation Output==
 
{| cellspacing=2
|Input:<br> [[File:Psim2.skymodel.png|300px]]
|simobserve:<br> [[File:Psim2.alma.out20.observe.png|300px]]
|-
|simanalyze image:<br> [[File:Psim2.alma.out20.image.png|300px]]
|simanalyze output:<br> [[File:Psim2.analysis.png|300px]]
|}
 
{{Simulations Intro}}
{{Checked 3.4.0}}

Latest revision as of 19:37, 12 June 2012

↵ Simulating Observations in CASA

Data

For this CASA Guide we will use a protoplanetary disk model from S. Wolf. If you use this FITS data for anything more than learning CASA, please cite Wolf & D'Angelo 2005.

Script with Explanation

Set simobserve as the current task and reset all parameters. 

# In CASA
default("simobserve")

Review the image coordinate system using task imhead. 

# This reports image header parameters in the Log Messages window
imhead("input50pc_672GHz.fits")

We now use the ia (image analysis) and qa (units and quantities) tools from the CASA Toolkit to find the image center. In comparison to tasks, tools are a more advanced way of manipulating data in CASA. You can learn more about tools using the tool reference manual.

When data are being manipulated with tools the data file must be explicitly opened and closed. 

# In CASA
ia.open("input50pc_672GHz.fits")

Next, get the right ascension and declination of the image center. We get the number of pixels along each axis using ia.shape. Then, we get the RA and Dec values for the center pixel using ia.toworld. 

# In CASA
axesLength = ia.shape()
# Divide the first two elements of axesLength by 2.
center_pixel = [ x / 2.0 for x in axesLength[:2] ]
# Feed center_pixel to ia.toworld and and save the RA and Dec to ra_radians and dec_radians
(ra_radians, dec_radians) = ia.toworld( center_pixel )['numeric'][:2]
ia.close()

Use the qa tool to convert the image center from radians to sexagesimal coordinates. 

ra_hms  = qa.formxxx(str(ra_radians)+"rad",format='hms',prec=5)
dec_dms = qa.formxxx(str(dec_radians)+"rad",format='dms',prec=5)

Let's call our project "psim2". This defines the root prefix for any output files from simobserve. 

project = "psim2"

We'll set skymodel to the FITS file downloaded, above, and leave all skymodel subparameters at their default values. simobserve will create CASA image psim2.skymodel. 

skymodel = "input50pc_672GHz.fits"

We will specify the sky position for the center of the observation and set the map size to the size of the model image. Since the model image is 2/3 arcseconds across, we should only need one pointing. In this case, pointingspacing and maptype can be left at their default values. 

setpointings       =  True
direction          =  "J2000 18h00m00.031s -22d59m59.6s"
mapsize            =  "0.76arcsec"

We do want to simulate an interferometric observation, so we set obsmode accordingly. We'll set totaltime to a 20-minute snapshot observation. 

obsmode            =  "int"
totaltime          =  "1200s"

We want to use the appropriate antenna configuration for the desired angular resolution. Configuration 20, alma.out20.cfg, is the largest "compact" configuration. 

antennalist        =  "alma.out20.cfg"

Now run simobserve. 

simobserve()

Now that we've simulated the visibility measurements, we want to generate an image from the simulated data. simanalyze makes this easy. We begin by setting project to the same prefix used in simobserve and setting image to True. 

default ("simanalyze")
project = "psim2"
image = True

We set modelimage to use the input FITS image when cleaning the simulated visibilities. We set the image size to 192 pixels square. 

modelimage = "input50pc_672GHz.fits"
vis = project + ".alma.out20.ms"
imsize = [192, 192]

Specify the number of iterations for cleaning, with proper threshold and weighting. 

niter = 10000
threshold = "1e-7Jy"
weighting = "natural"

We'd like to calculate a difference and fidelity image, but we don't need to see the uv coverage. 

analyze = True  
showuv = False
showresidual = True  
showconvolved = True

Plot both to the screen and PNG files with lots of messages. 

graphics = "both"
verbose = True
overwrite = True

Run simanalyze. 

simanalyze()

Simulation Output

Input:
 simobserve:
simanalyze image:
 simanalyze output:

↵ Simulating Observations in CASA

Last checked on CASA Version 3.4.0.

Retrieved from "https://casaguides.nrao.edu/index.php?title=Protoplanetary_Disk_Simulation_(CASA_3.4)&oldid=12363"