ALMA Cycle 4 Imaging Pipeline Reprocessing

About This Guide

This guide describes some examples for perfecting the interferometric imaging products from the ALMA Cycle 4 Pipeline. After Section #Restore Pipeline Calibration and Prepare for Re-imaging, each reprocessing option is self-contained.

Note that the scripts described in this guide have only been tested in Linux.

Getting and Starting CASA

If you do not already have CASA installed on your machine, you will have to download and install it.

Download and installation instructions are available here:

http://casa.nrao.edu/casa_obtaining.shtml

CASA 4.7.0 or later is required to reprocess ALMA Cycle 4 data using the scripts in this guide.

NOTE: To use pipeline tasks, you must start CASA with

casa --pipeline

Restore Pipeline Calibration and Prepare for Re-imaging (all Options)

STEP 1: Follow instructions in your README for restoring pipeline calibrated data using the scriptForPI.py. NOTE: the SPACESAVING parameter cannot be larger than 1

STEP 2: Change to directory that contains the calibrated data (i.e. *.ms) called "calibrated/working" after the pipeline restore and start CASA 4.7.0 or later.

casa --pipeline

STEP 3: Run the following command in CASA to copy the pipeline file that contains the frequency ranges used to create the continuum images and the continuum subtraction to the directory you will be working in.

os.system('cp ../../calibration/uid*cont.dat ./cont.dat')

Restore Pipeline Continuum Subtraction and Manually Make Image Products

## Edit the USER SET INPUTS section below and then execute
## this script (note it must be in the 'calibrated/working' directory.

import glob as glob
__rethrow_casa_exceptions = True
pipelinemode='automatic'
context = h_init()

###########################################################
## USER SET INPUTS

## Select a title for the weblog
context.project_summary.proposal_code='Restore Continuum Subtraction'

############################################################

## Make a list of all uv-datasets appended with *.split.cal
MyVis=glob.glob('*.ms')

try:
    ## Load the *.ms files into the pipeline
    hifa_importdata(vis=MyVis, pipelinemode=pipelinemode)

    ## Split off the science target data into its own ms (called
    ## *target.ms) and apply science target specific flags
    hif_mstransform(pipelinemode=pipelinemode)
    hifa_flagtargets(pipelinemode=pipelinemode)

    ## Fit and subtract the continuum using the cont.dat for all spws all fields
    hif_uvcontfit(pipelinemode=pipelinemode)
    hif_uvcontsub(pipelinemode=pipelinemode)

finally:
    h_save()

Make Images Manually

At this point you will have created a *target.ms for each execution of your SB. Each of these measurement sets contains the original calibrated continuum + line data in the DATA column and the calibrated continuum subtracted data in the the CORRECTED column. The new CASA task for imaging tclean (which is used by the ALMA Pipeline) allows the user to select which column to use for imaging. tclean also allows a list for the vis parameter so that it is not necessary to concat the data before imaging.

**NOTE:** If you think you might want to self-calibrate your data using either the continuum or line emission it is ESSENTIAL that you first split off the column that you want to operate on before imaging. Otherwise, the CORRECTED column containing the continuum subtracted data will be overwritten when applycal is run during the self-calibration process.

To manually clean your data at this stage, there are two options:

1. Use modified versions of the relevant tclean commands from the "logs/<MOUS_name>.casa_commands.log". These are the exact commands originally run by the imaging pipeline to produce your imaging products.
   • They will contain within them the frequency ranges (from the cont.dat) used for making the various images.
   • There will be two tclean commands per image product, the first with an image name containing iter0 only makes a dirty image, while the second with iter1 makes a cleaned image.
   • For example to make the aggregate continuum image but with interactive clean masking, simply copy the corresponding iter1 command (it will contain all of the spw numbers in its name), but set interactive=True, calcpsf=True, and calcres=True. If you are using the *.target.ms file(s) you can keep datacolumn='DATA'. If you have split off the DATA column and have applied self-calibration, you will want to image the datacolumn='CORRECTED'.
2. Use examples on the casaguide page TCLEAN_and_ALMA to formulate your own special purpose commands.

Restore Pipeline Continuum Subtraction and Make Pipeline Aggregate Continuum Image With All Channels

## Edit the USER SET INPUTS section below and then execute
## this script (note it must be in the 'calibrated/working' directory.

import glob as glob
__rethrow_casa_exceptions = True
pipelinemode='automatic'
context = h_init()

###########################################################
## USER SET INPUTS

## Select a title for the weblog
context.project_summary.proposal_code='NEW AGGREGATE CONT'

############################################################

## Move cont.dat to another name if it exists
os.system('mv cont.dat original.cont.dat')

## Make a list of all uv-datasets appended with *.split.cal
MyVis=glob.glob('*.ms')

try:
    ## Load the *.ms files into the pipeline
    hifa_importdata(vis=MyVis, pipelinemode=pipelinemode)

    ## Split off the science target data into its own ms (called
    ## *target.ms) and apply science target specific flags
    hif_mstransform(pipelinemode=pipelinemode)
    hifa_flagtargets(pipelinemode=pipelinemode)

    ## Skip the continuum subtraction steps and make an aggregate 
    ## continuum image with all unflagged channels (file named 
    ## cont.dat should NOT be present in directory).
    hif_makeimlist(specmode='cont',pipelinemode=pipelinemode)
    hif_makeimages(pipelinemode=pipelinemode)

    ## Export new images to fits format if desired.
    hif_exportdata(pipelinemode=pipelinemode)

finally:
    h_save()

Revise the cont.dat Before Pipeline Continuum Subtraction and Remake Pipeline Images

## Edit the cont.dat file(s) for the spw(s) you want 
## to change the continuum subtraction for. In this example 
## spw 17 was changed.

## Edit the USER SET INPUTS section below and then execute
## this script (note it must be in the 'calibrated/working' directory.

import glob as glob
__rethrow_casa_exceptions = True
pipelinemode='automatic'
context = h_init()

###########################################################
## USER SET INPUTS

## Select a title for the weblog
context.project_summary.proposal_code = 'NEW CONTSUB' 

## Select spw(s) that have new cont.dat parameters
## If all spws have changed use MySpw=''
MySpw='17'

############################################################

## Make a list of all uv-datasets appended with *.split.cal
MyVis=glob.glob('*.ms')

try:
    ## Load the *.ms files into the pipeline
    hifa_importdata(vis=MyVis, pipelinemode=pipelinemode)

    ## Split off the science target data into its own ms (called
    ## *target.ms) and apply science target specific flags
    hif_mstransform(pipelinemode=pipelinemode)
    hifa_flagtargets(pipelinemode=pipelinemode)

    ## Fit and subtract the continuum using revised cont.dat for all spws
    hif_uvcontfit(pipelinemode=pipelinemode)
    hif_uvcontsub(pipelinemode=pipelinemode)

    ## Make new per spw continuum for revised spw(s) and new aggregate cont
    hif_makeimlist(specmode='mfs',spw=MySpw)
    hif_makeimages(pipelinemode=pipelinemode)
    hif_makeimlist(specmode='cont',pipelinemode=pipelinemode) 
    hif_makeimages(pipelinemode=pipelinemode)    

    ## Make new continuum subtracted cube for revised spw(s)
    hif_makeimlist(specmode='cube',spw=MySpw,pipelinemode=pipelinemode) 
    hif_makeimages(pipelinemode=pipelinemode)

    ## Export new images to fits format if desired.
    hif_exportdata(pipelinemode=pipelinemode)

finally:
    h_save()

Restore Pipeline Continuum Subtraction for Subset of SPWs and Fields and Use Channel Binning for Pipeline Imaging of Cubes

## Edit the USER SET INPUTS section below and then execute
## this script (note it must be in the 'calibrated/working' directory.

import glob as glob
__rethrow_casa_exceptions = True
pipelinemode='automatic'
context = h_init()

###########################################################
## USER SET INPUTS

## Select a title for the weblog
context.project_summary.proposal_code = 'SUBSET CUBE IMAGING' 

## Select spw(s) to image and channel binning for each spcified
## MySpw. All spws listed in MySpw must have a corresponding MyNbins
## entry, even if it is 1 for no binning.
MySpw='17,23'
MyNbins='17:8,23:2'

## Select subset of sources to image by field name.
## To select all fields, set MyFields=''
MyFields='CoolSource1,CoolSource2'

## Select Briggs Robust factor for data weighting (affects angular 
## resolution of images)
MyRobust=1.5

############################################################

## Make a list of all uv-datasets appended with *.split.cal
MyVis=glob.glob('*.ms')

try:
    ## Load the *.ms files into the pipeline
    hifa_importdata(vis=MyVis, pipelinemode=pipelinemode)

    ## Split off the science target data into its own ms (called
    ## *target.ms) and apply science target specific flags
    ## In this example we split off all science targets and science 
    ## spws, however these steps could also contain the spw and field
    ## selections
    hif_mstransform(pipelinemode=pipelinemode)
    hifa_flagtargets(pipelinemode=pipelinemode)

    ## Fit and subtract the continuum using existing cont.dat
    ## for selected spws and fields only.
    hif_uvcontfit(spw=MySpw,field=MyFields,pipelinemode=pipelinemode)
    hif_uvcontsub(spw=MySpw,field=MyFields,pipelinemode=pipelinemode)   

    ## Make new continuum subtracted cube for selected spw(s) and fields
    hif_makeimlist(specmode='cube',spw=MySpw,nbins=MyNbins,field=MyFields,
                   pipelinemode=pipelinemode) 
    hif_makeimages(robust=MyRobust,pipelinemode=pipelinemode)

    ## Export new images to fits format if desired.
    hif_exportdata(pipelinemode=pipelinemode)

finally:
    h_save()