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gocontinuum's Introduction

GoContinuum

DOI

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

The code has been tested with CASA 5.x versions and python 2.7. In addition the code needs the following python packages:

  • numpy
  • scipy
  • matplotlib
  • astropy

Optional:

  • YCLEAN (Contreras 2018; use the command line flag --skip YCLEAN if not available)

Data structure

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

  • 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].. If the dirty directory does not exist or is empty, dirty files are calculated from each visibility ms in uvdata. IMPORTANT goco checks for FITS files in the dirty directory with the same root as the ms. If the naming is different then you can skip the dirty checking step using the option --skip DIRTY when calling goco. Parameters for producing the dirty images are defined in the configuration file (see below)

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 numbering starts from 1. The visibility files must end with .ms

By default these directories should be in the upper BASE directory, but this can be modified using the command line flag -b BASE or --base BASE. 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

Applying a calibration table from e.g. self-calibration can be applied before or within the code.

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.
  • Apply calibration table if needed.
  • 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).
  • Apply calibration table if needed.
  • 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:

./goco <field_name>

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

./goco --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:

./goco --noredo [--neb <number_of_ebs>] <field_name>

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

./goco --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.

Command line options:

Usage: goco [-h|--help] [--noredo] [-s|--silent] [--vv] [--dirty] [--skip step [step ...]] [--put_rms] [--pos x y] [--max] field

Parameters:
  field                 Field name

Options:
  -h, --help            Help
  --neb                 Number of EBs
  --noredo              Skip steps some steps already finished
  -s, --silent          Set verbose=0 in pipeline.sh
  --vv                  Set verbose level to debug
  --dirty               Compute dirty images if dirty directory does not exist
  --skip                Skip given steps (see --steps)
  --steps               List available steps
  --put_rms             Put rms in image headers
  --pos                 Position where to extract spectrum
  --max                 Use max to determine position of peak

Skip steps values are: DIRTY, AFOLI, CONTSUB, SPLIT, YCLEAN and PBCLEAN.

The cfg file

An example file is in the example directory. The configuration file .cfg must follow the following example:

[DEFAULT]
field = field_name
imsize = 1920 1920
cellsize = 0.03arcsec
spws = 0,1,2,3

[dirty]
robust = 2.0
parallel = true

[afoli]
flagchans = 12~20 30~40
levels = 0.03 0.05 0.1 0.15 0.20 0.25
level_mode = linear

[split_ms]
datacolumn = data

[lineapplycal]
gaintable = phase.cal

[contapplycal]
gaintable = amp.cal

[pbclean]
pbmask = 0.2

[yclean]
vlsr = 0.0
dir = /dir/to/yclean
chanranges = 0~1930 1910~3839
joinchans = 0~1920 11~1929

Parameters in the DEFAULT section are applied to all the other sections if not specified within the section. If selfcal has not been applied or comes from a split file, then datacolumn should be set to data.

The flagchans in afoli allows the addition of specific flags for channels. If the levels pararmeter is included, the program will calculate the channels masked at these levels. The channels with valid data are determined where continuum[i]/final_continuum == 1+levels[j] where continuum[i] is the continuum from iteration i of the sigma_clip function. The kind of interpolation between iterations can be controled with level_mode.

Self-calibration tables can be applied after the uvcontsub and split steps for lines and continuum respectively. For more than one eb observations and each with its own calibration table then there are 2 ways to specify the calibration tables. For example, observations with an EB with 2 calibration tables and other EB with 1, the first alternative is:

[lineapplycal1]
gaintable = eb1.table1.cal eb1.table2.cal

[lineapplycal2]
gaintable = eb2.table1.cal

or

[lineapplycal]
gaintable = eb1.table1.cal eb1.table2.cal, eb2.table1.cal

The chanranges parameter will split the data in different cubes, whilst joinchans are the channels used to join these cubes. These can be ommited if the data won't be splitted into smaller cubes. The vlsr is in km/s. Rest frequencies for each spectral window in spw can be given with the restfreqs parameter in the yclean section.

If there are spectral windows with different sizes then the yclean section can take values of chanranges and joinchans for each spw. For example, if there are 2 spws, the first one with 3840 channels and want to split it in around half, and the second one with 1920 channels and use all the channels, then the yclean section would look like:

[yclean]
spws = 0,1
vlsr = 0.0
dir = /dir/to/yclean
freqs = 234.525GHz 232.025GHz
chanrange0 = 0~1930 1910~3839
joinchans0 = 0~1920 11~1929

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