xinglunju / GoContinuum

Find continuum channels with asymmetric sigma-clipping and produce images

GoContinuum

This program uses an asymmetric sigma clip algorithm to find line-free channels in the spectrum of the maximum of a data cube. It then uses these channels to produce a continuum subtracted ms and quality assurance continuum images.

Requirements

Dependencies

In addition to the most recent version of CASA, the code need the following python packages:

• numpy
• scipy
• matplotlib
• astropy

Data structure

The main program runs from the pipeline.sh script. It requires the input data to be in the following directories:

• final_uvdata for the split visibilities ms.
• dirty for the dirty FITS files separated by spectral windows (in some cases in CASA format, see below). The spectral window must be included in the file name, with the substring .spw[0-3]..

In both cases the file names have to start with:

• <field_name> if the observations have 1 EB.
• <field_name>.<EB_number> if the observations have more than 1 EB. The EB number starts from 1.

By default these directories should be in the upper directory, but this can be modified by changing the BASE parameter defined at the beginning of the script. A configuration file named <field_name>.cfg needs to be created in the BASE directory (see below for details about this file).

All the directories with the products (e.g. plots) are created by the script if needed.

Algorithm implementation

The ms files in final_uvdata are assumed to be self-calibrated (i.e. they have a corrected data column).

For each EB:

• Search for the maximum value in each SWP (neglecting the 10 channels at the edges)
• Combine maximum values, reject the one that is an outlier and take the average among the other 3 values to define the central source.
• Extract the spectra at the central source.
• Find the continuum channels from the spetrum of the central source:
  1. Mask channels at the edges of the spectrum.
  2. Applying an asymmetrical sigma clip with sigma_upper=1.3 and sigma_lower=3.0 to mask channels with lines.
  3. Unmask channels with line emission that span for less than 3 continuous channels (2 raw channels correspond to 1 spectral resolution).
  4. Save the mask.

For lines then:

• Run uvcontsub (in CASA) for each EB using the mask to subtract the continuum.
• If more than 1 EB, concatenate the visibilities.
• Use YCLEAN with the continuum subtracted visibilities.

For continuum then:

• Split the visibilities and average channels:
  1. Split using the channels in the mask (files with cont_avg).
  2. Split without any masking (files with allchannels_avg).
• If more than 1 EB, concatenate the visibilities.
• Make quality control images using automatic PB cleaning for both visibility sets above.

Basic usage

To apply the algorithm above is as easy as running:

./pipeline.sh <field_name>

If there are more than 1 EB in the observations, then run:

./pipeline.sh --neb <number_of_ebs> <field_name>

The program will automatically run all the steps, and if the files already exist it will overwrite or delete them. If only a specific step has to be run (e.g. the last CLEAN), then it is recommended to delete the files manually and run:

./pipeline.sh --noredo [--neb <number_of_ebs>] <field_name>

The continuum finding will run either way on the saved spectra.

It is possible to run the program at a specific position with:

./pipeline.sh --pos <x pixel> <y pixel> <field_name>

IMPORTANT 1: the positions are zero based.

IMPORTANT 2: different positions for each EB has not been implemented. The recommendation is to produce images with the same size and pixel size for each EB if using this method.

The cfg file

The configuration file .cfg must follow the following example:

[field_name]
imsize = 1024 1024
cellsize = 0.04arcsec