Data Analysis

Le programme blanc 2015 a soutenu le financement d’un serveur de post-traitement de données, porté par la DIO, et utilisé en partie pour analyser les données ALMA. Cette machine –appelée « Johannes » – a été installée fin 2015 par la DIO.

Pour demander un compte sur Johannes, contacter : admin.dio@obspm.fr et mettre en copie raphael.moreno@obspm.fr

ALMA data reduction and Imaging on Johannes

Open an account on Johannes
* You have to request an account on Johannes, the ALMA post-processing
computer at the Paris Observatory. Please specify the volume space you would
need to reduce your data as well as the purpose of this account creation.

Email the Paris Observatory DIO as well as Raphael Moreno (LESIA) for the ALMA/NOEMA Paris Federactive Action

TIP: mailto:admin.dio@obspm.fr[admin.dio@obspm.fr] +
mailto:raphael.moreno@obspm.fr[raphael.moreno@obspm.fr]

You can then login on Johannes with your LDAP ids and passwords (same as webmail) and get into your ALMA directory.

johannes:~$ cd /johannes/alma/yourlogin

Download the raw data

From your account on Johannes:: Run the script
downloadRequestXXXXXXX.sh

johannes:~$ chmod a+x downloadRequestXXXXXXX.sh
johannes:~$ ./downloadRequestXXXXXXX.sh

* Untar the directory. The project directory contains sub-directories that
corresponds to individual observations (mous_id). There could be several
observations for the same science goal.

* Enter into each sub-directory to reprocess each data, ie

johannes:~$ cd 2013.1.02197.S/science_goal.uid___A002_X2de_X2da/group.uid___
A002_X2fe_X2ab/member.uid___A001_X1fa_X1bc
johannes:~$ ls
calibration log product qa raw README script

* Take a look to the README file as well as the content of the product/ directory
* Enter into the script directoty in order to re-run the pipeline

johannes:~$ cd script

Data calibration with casa

Run the pipeline::
* In order to run the pipeline, you need to use a specific version of casa. The
command module will list all the casa versions installed on Johannes.

johannes:~$ module avail casa
casa/3.3 casa/4.1 casa/4.3 casa/4.5.1 casa/4.5.3 casa/4.7 casa/5.1.1
casa/3.4 casa/4.2 casa/4.5 casa/4.5.2 casa/4.6 casa/4.7.2

johannes:~$ module load casa/4.5

* Run casa and execute the pipeline data reduction script

johannes:~$ casa –pipeline

casa> SPACESAVINGS=3
casa> execfile(‘scriptForPI.py’)

* If the version of casa is not the correct one, load the required module (see
above) and restart casa. The pipeline should produce a new directory called calibrated

johannes:~$ ls
calibrated calibration log product qa raw README script

* Inside this new directory (calibrated), you should find a measurement set called
calibrated.ms
* This is the calibrated data set as produced by the pipeline

Imaging

TIP: Now the calibration is done. You still have to produce an image from the calibratred
visibilities. In order to do so, you can either use casa or export your dataset into GILDAS.

Converting the data to GILDAS:: Using casa, you need to run:

casa>
sourceFreq= ‘XXX.xxxGHz’ # here I used the observed frequency
lineName=’xxx’
sourceName=’xxxx’

split(vis=calibrated.ms’, # the file with all the visibilities
outputvis=sourceName+’_’+lineName+’.ms’,
field = sourceName,
spw=’2,29’, # the spws of line
width = ‘2’, # here we can average channels to decrease the spectral resolution
datacolumn=’DATA’,
keepflags= False)

mstransform(vis=sourceName+’_’+lineName+’.ms’,
outputvis=sourceName+’_’+lineName+’.mstrans.ms’,
datacolumn=’DATA’,
regridms = True,
combinespws=True,
restfreq = sourceFreq, # the observed frequency
outframe=’LSRK’)

exportuvfits(vis=souname+’_’+lineName+’.mstrans.ms’,
fitsfile=sourceName+’_’+lineName+’.uvfits’,
datacolumn=’data’)

johannes:~$ casa> exit

On GILDAS/ mapping::
Convert the uvfits into uvt in order to do the imaging within GILDAS

johannes:~$ mapping

mapping> @fits_to_uvt sourceName_lineName sourceName_LineName FREQUENCY 115271 VELOCITY 0 LINE CO10

The frequency in MHz. Instead of setting the velocity 0 we can put the systemic velocity as well, but I think then we should use the rest
frequency, not sure about it. Here the example is for the CO(1-0) with at the rest frequecy.

mapping> read uv sourceName_LineName
mapping> go uvmap
mapping> go view

TIP: Now, the last thing is the cleaning. This requires more interaction with the data. However, you can start with a first attempt by doing
the following commands