User Parameters - Spectral-line Imaging

There are several steps involved in running the spectral-line imaging, with several optional pre-processing steps:

1. A nominated channel range can optionally be copied to a new MS with mssplit.
2. The gains solution from the continuum self-calibration can be applied to the spectral-line MS using ccalapply.
3. The continuum can be subtracted from the spectral-line MS using ccontsubtract The continuum is represented by either the clean model from the continuum imaging, or – as the default – a model image constructed by Cmodel from the component catalogue generated by Selavy.

Following this pre-processing, the resulting MS is imaged by the simager task, creating a set of spectral cubes. At this point, no mosaicking of these is done, but this will be added in a future version of the pipeline.

The variables presented below work in the same manner as those for the continuum imaging, albeit with names that clearly refer to the spectral-imaging.

Variable	Default	Parset equivalent	Description
DO_SPECTRAL_IMAGING	false	none	Whether to do the spectral-line imaging
Preparation of spectral dataset
DO_COPY_SL	false	none	Whether to copy a channel range of the original full-spectral-resolution measurement set into a new MS. If the original MS is original.ms, this will create original_SL.ms.
CHAN_RANGE_SL_SCIENCE	“1-NUM_CHAN_SCIENCE“	channel (mssplit (Measurement Splitting/Averaging Utility))	The range of channels to copy from the original dataset (1-based).
TILENCHAN_SL	1	stman.tilenchan (mssplit (Measurement Splitting/Averaging Utility))	The number of channels in the tile size used for the new MS. The tile size defines the minimum amount read at a time. Since the simager will process single channels, making this 1 (the default) means the simager workers only read what they need to .
DO_APPLY_CAL_SL	false	none	Whether to apply the gains calibration determined from the continuum self-calibration (see GAINS_CAL_TABLE in User Parameters - Continuum Self-calibration).
DO_CONT_SUB_SL	false	none	Whether to subtract a continuum model from the spectral-line dataset. If true, the clean model from the continuum imaging will be used to represent the continuum, and this will be subtracted from the spectral-line dataset (either the original full-spectral-resolution one, or the reduced-channel-range copy), which gets overwritten.
Continuum subtraction
CONTSUB_METHOD	Cmodel	none	This defines which method is used to determine the continuum that is to be subtracted. It can take one of three values: Cmodel (the default), which uses a model image constructed by Cmodel (cmodel (Model Image Generator)) from a continuum components catalogue generated by Selavy (Selavy Basics); Components, which uses the Selavy catalogue directly by in the form of components; or CleanModel, in which case the clean model from the continuum imaging will be used.
CONTSUB_SELAVY_NSUBX	6	nsubx (Selavy Basics)	Division of image in x-direction for source-finding
CONTSUB_SELAVY_NSUBY	3	nsuby (Selavy Basics)	Division of image in y-direction for source-finding
CONTSUB_SELAVY_THRESHOLD	6	snrCut (Selavy Basics)	SNR threshold for detection with Selavy in determining components to go into the continuum model.
CONTSUB_MODEL_FLUX_LIMIT	0mJy	flux_limit (cmodel (Model Image Generator))	Flux limit applied to component catalogue - only components brighter than this will be included in the model image. Parameter takes the form of a number+units string. Default (0mJy) implies all compoennts are used.
Basic variables for imaging
NUM_CPUS_SPECIMG_SCI	2000	none	The total number of processors allocated to the spectral-imaging job. One will be the master, while the rest will be devoted to imaging individual channels.
CPUS_PER_CORE_SPEC_IMAGING	20	none	The number of processors per node to use (max 20).
IMAGE_BASE_SPECTRAL	i.cube	Helps form Images.name (simager)	The base name for image cubes: if IMAGE_BASE_SPECTRAL=i.blah then we’ll get image.i.blah, image.i.blah.restored, psf.i.blah etc
DIRECTION_SCI	none	Images.direction (simager)	The direction parameter for the image cubes, i.e. the central position. Can be left out, in which case it will be determined from the measurement set by mslist. This is the same input parameter as that used for the continuum imaging.
NUM_PIXELS_SPECTRAL	2048	Images.shape (simager)	The number of spatial pixels along the side for the image cubes. Needs to be specified (unlike the continuum imaging case).
CELLSIZE_SPECTRAL	10	Images.cellsize (simager)	The spatial pixel size for the image cubes. Must be specified.
REST_FREQUENCY_SPECTRAL	HI	Images.restFrequency (simager)	The rest frequency for the cube. Can be a quantity string (eg. 1234.567MHz), or the special string ‘HI’ (which is 1420.405751786 MHz). If blank, no rest frequency will be written to the cube.
Gridding
GRIDDER_SPECTRAL_SNAPSHOT_IMAGING	true	snapshotimaging (Gridders)	Whether to use snapshot imaging when gridding.
GRIDDER_SPECTRAL_SNAPSHOT_WTOL	2600	snapshotimaging.wtolerance (Gridders)	The wtolerance parameter controlling how frequently to snapshot.
GRIDDER_SPECTRAL_WMAX	2600	WProject.wmax (Gridders)	The wmax parameter for the gridder.
GRIDDER_SPECTRAL_NWPLANES	99	WProject.nwplanes (Gridders)	The nwplanes parameter for the gridder.
GRIDDER_SPECTRAL_OVERSAMPLE	4	WProject.oversample (Gridders)	The oversampling factor for the gridder.
GRIDDER_SPECTRAL_MAXSUPPORT	512	WProject.maxsupport (Gridders)	The maxsupport parameter for the gridder.
Cleaning
SOLVER_SPECTRAL	Clean	solver (Solvers)	Which solver to use. You will mostly want to leave this as ‘Clean’, but there is a ‘Dirty’ solver available.
CLEAN_SPECTRAL_ALGORITHM	Basisfunction	Clean.algorithm (Solvers)	The name of the clean algorithm to use. Note that the default has changed to ‘Basisfunction’, as we don’t need the multi-frequency capabilities of ‘BasisfunctionMFS’.
CLEAN_SPECTRAL_MINORCYCLE_NITER	500	Clean.niter (Solvers)	The number of iterations for the minor cycle clean.
CLEAN_SPECTRAL_GAIN	0.5	Clean.gain (Solvers)	The loop gain (fraction of peak subtracted per minor cycle).
CLEAN_SPECTRAL_SCALES	“[0,3,10]”	Clean.scales (Solvers)	Set of scales (in pixels) to use with the multi-scale clean.
CLEAN_SPECTRAL_THRESHOLD_MINORCYCLE	“[30%, 0.9mJy]”	threshold.minorcycle (Solvers)	Threshold for the minor cycle loop.
CLEAN_SPECTRAL_THRESHOLD_MAJORCYCLE	1mJy	threshold.majorcycle (Solvers)	The target peak residual. Major cycles stop if this is reached. A negative number ensures all major cycles requested are done.
CLEAN_SPECTRAL_NUM_MAJORCYCLES	0	ncycles (Solvers)	Number of major cycles.
CLEAN_WRITE_AT_MAJOR_CYCLE	false	Images.writeAtMajorCycle (simager)	If true, the intermediate images will be written (with a .cycle suffix) after the end of each major cycle.
Preconditioning
PRECONDITIONER_LIST_SPECTRAL	“[Wiener, GaussianTaper]”	preconditioner.Names (Solvers)	List of preconditioners to apply.
PRECONDITIONER_SPECTRAL_GAUSS_TAPER	“[50arcsec, 50arcsec, 0deg]”	preconditioner.GaussianTaper (Solvers)	Size of the Gaussian taper - either single value (for circular taper) or 3 values giving an elliptical size.
PRECONDITIONER_SPECTRAL_WIENER_ROBUSTNESS	0.5	preconditioner.Wiener.robustness (Solvers)	Robustness value for the Wiener filter.
PRECONDITIONER_SPECTRAL_WIENER_TAPER	“”	preconditioner.Wiener.taper (Solvers)	Size of gaussian taper applied in image domain to Wiener filter. Ignored if blank (ie. тАЬтАЭ).
Restoring
RESTORE_SPECTRAL	true	restore (simager)	Whether to restore the image cubes.
RESTORING_BEAM_SPECTRAL	fit	restore.beam (simager)	Restoring beam to use: ‘fit’ will fit the PSF in each channel separately to determine the appropriate beam for that channel, else give a size (such as 30arcsec, or тАЬ[30arcsec, 30arcsec, 0deg]тАЭ).
RESTORING_BEAM_REFERENCE	mid	restore.beamReference (simager)	Which channel to use as the reference when writing the restoring beam to the image cube. Can be an integer as the channel number (0-based), or one of ‘mid’ (the middle channel), ‘first’ or ‘last’
RESTORING_BEAM_LOG	beamLog.IMAGE.txt (with IMAGE from IMAGE_BASE_SPECTRAL)	restore.beamLog (simager)	The ASCII text file to which will be written the restoring beam for each channel. If blank, no such file will be written.