imcontsub

The purpose of this software is to subtract continuum in a parallel/distributed environment or on a single computer system. The software leverages MPI, however can be run on a simple laptop or a large supercomputer.

The imcontsub task is based on the version of the ACES robust_contsub.py script from Dec 2019. It performs the following processing for each spectrum:

• exclude outliers (top and bottom 5%),
• do approximate linear fit of the spectrum (using every 10th data point)
• subtract off the linear fit to remove source spectral index to 1st order
• determine mask based on threshold and IQR relative to median (see below)
• use mask to fit original channels with polynomial of given order
• subtract fit and write out residual spectrum

Running the program

It can be run with the following command, where “config.in” is a file containing the configuration parameters described in the next section.

$ <MPI wrapper> imcontsub -c config.in

Configuration Parameters

Parset parameters understood by imcontsub are given in the following table (all parameters must have imcontsub prefix, i.e. imcontsub.order).

Parameter	Type	Default	Description
inputfitscube	string	None	Image cube to work with. The input file has to be in FITS format. It is read and left unchanged.
outputfitscube	string	generated	The name of the cube to write the results to. If the file already exists, it will be overwritten. If the output name is left unspecified, it is generated from the input name: mycube.fits -> mycube.contsub.fits
order	int	2	The order of the polynomial used to fit for the continuum.
threshold	float	2.0	The threshold (in robust rms units) used to decide which channels to include in the fit for the continuum. A channel is included if it is not flagged and: abs(pixval-median) < threshold*rms where rms is estimated from the IQR (inter quartile range)

Example

# The input fits cube
imcontsub.inputfitscube                           = mycube.fits
# The output fits cube
imcontsub.outputfitscube                          = mycube.contsub.fits
# The polynomial order - doing a linear fit
imcontsub.order                                   = 1
# The threshold - include channels within 2.5 sigma
imcontsub.threshold                               = 2.5