User Parameters - Continuum imaging

Summary

The parameters listed here allow the user to configure the parset and the slurm job for continuum imaging of the science field. The defaults have been set based on experience with science commissioning and ASKAP Early Science, using the 12-antenna array. If you are processing different data sets, adjusting these defaults may be necessary.

Some of the parameters can be set to blank, to allow cimager to choose appropriate values based on its “advise” capability (which involves examining the dataset and setting appropriate values for some parameters.

For most observations to date, there is a single phase centre that applies for all beams. Thus, if advise is used to determine the image centre, the same direction will be used for each beam. This is the way the BETA processing was done, and in this case the image size must be chosen to be big enough to encompass all beams. This behaviour is applied when IMAGE_AT_BEAM_CENTRES=false.

The preferred behaviour, however, is to set a different image centre per beam, as this allows a smaller image to be made when imaging. To do this, the footprint.py tool is used to determine the locations of the centres of each beam. The footprint specification is determined preferentially from the scheduling block parset, or (if not available there) from the parameters described at User Parameters - Mosaicking. To use this mode, set IMAGE_AT_BEAM_CENTRES=true.

While the default application used for the imaging is cimager, it is possible to use the newer imager (imager). Much of the functionality will be identical for continuum data (imager was developed initially as a better spectral-line imaging tool).

Self-calibration

The default approach for continuum imaging is to do it in conjunction with self-calibration. The algorithm here is as follows:

1. Image the data with cimager or imager

2. Run source-finding with Selavy with a relatively large threshold (unless we are using option 3c. below)

3. Use the results to calibrate the antenna-based gains by either:

   1. Create a component parset from the resulting component catalogue and use this parset in ccalibrator

   2. Create a model image from the component catalogue, and use in ccalibrator

   3. Use the clean model image from the most recent imaging as the model for ccalibrator (no source-finding will be done)

4. Re-run imaging, applying the latest gains table

5. Repeat steps 2-5 for a given number of loops

Each loop gets its own directory, where the intermediate images, source-finding results, and gains calibration table are stored. At the end, the final gains calibration table is kept in the main output directory (as this can then be used by the spectral-line imaging pipeline).

There are two options for how this is run. The first (MULTI_JOB_SELFCAL=true) launches a separate slurm job for each imaging task, and each “calibration” task - the calibration job incorporates the selavy, cmodel and ccalibrator tasks. The latter uses a single node only. If MULTI_JOB_SELFCAL=false, these are all incorporated into one slurm job, including all loops.

Some parameters are allowed to vary with the loop number of the self-calibration. This way, you can decrease, say, the detection threshold, or increase the number of major cycles, as the calibration steadily improves. These parameters are for:

• Deconvolution: CLEAN_ALGORITHM, CLEAN_GAIN, CLEAN_PSFWIDTH, CLEAN_THRESHOLD_MAJORCYCLE, CLEAN_NUM_MAJORCYCLES, CLEAN_MINORCYCLE_NITER, CLEAN_THRESHOLD_MINORCYCLE and CLEAN_SCALES

• Preconditioning: PRECONDITIONER_LIST, PRECONDITIONER_GAUSS_TAPER, PRECONDITIONER_GAUSS_TAPER_IS_PSF, PRECONDITIONER_GAUSS_TAPER_TOL, PRECONDITIONER_WIENER_ROBUSTNESS, and PRECONDITIONER_WIENER_TAPER

• Self-calibration: SELFCAL_SELAVY_THRESHOLD, SELFCAL_INTERVAL and SELFCAL_NORMALISE_GAINS

• Data selection in imaging: CIMAGER_MINUV and CIMAGER_MAXUV

• Data selection in calibration: CCALIBRATOR_MINUV and CCALIBRATOR_MAXUV

To use this mode, the values for these parameters should be given as an array in the form SELFCAL_INTERVAL="[1800,1800,900,300]", or, when the parameter would take an array of values, those arrays should be separated by semi-colons (with a space on either side): CLEAN_SCALES="[0] ; [0,20] ; [0,20,120,240] ; [0,20,120,240,480]".

The size of these arrays should be one more than SELFCAL_NUM_LOOPS. This is because loop 0 is just the imaging, and it is followed by SELFCAL_NUM_LOOPS loops of source-find–model–calibrate–image. Only the parameters related to the imaging (the deconvolution & preconditioning parameters in the list above) have the first element of their array used. If a single value is given for these parameters, it is used for every loop.

Instead of preconditioning, it is possible to use traditional weighting through the the use of TRADITIONAL_WEIGHT_PARAM_LIST and TRADITIONAL_WEIGHT_ROBUSTNESS, which can be loop dependent as well.

Once the gains solution has been determined, it can be applied directly to the continuum measurement set, creating a copy in the process. This is necessary for continuum cube processing, and for archiving purposes. This work is done as a separate slurm job, that starts upon completion of the self-calibration job.

There is a prototype option available (using SELFCAL_MASK_CLEAN_MODEL) that allows the clean model that is used for calibration to be modified - for example to clip negatives or low signal-to-noise ratio pixels. Two strategies are available for clipping, parameterised by SELFCAL_MASK_STRATEGY:

1. threshold: Simple threshold-based masking using fixed or sigma-based values.

2. adaptive: More sophisticated masking using local statistics and Gaussian filtering to determine the threshold. This would be useful for data with a significantly varying background, or high sidelobe noise.

This masking only alters the local image used by the calibration task. All imager products are left intact.

External calibration

A prototype option has been provided to allow the selfcal process to start with a phase-only calibration against a user-provided source catalogue (using the EXTERNAL_CATALOGUE parameter). This catalogue is used to create a model image, which is then used by ccalibrator to do phase-only calibration of the data. This is done prior to imaging, so that the first image has phases calibrated to the positions of sources in the catalogue. This can help improve the quality of the first image used in the selfcal. Self-calibration then proceeds as normal, with subsequent calibration steps using the model derived from that initial image.

Two special values for EXTERNAL_CATALOGUE are recognised: racs_mid or racs_low, which allow the querying of the respective RACS whole-sky catalogues through the sky model service interface in cmodel. This mode also provides for the application of primary-beam attenuation via the same interface used in linmos.

Leakage correction

The pipeline now has a feature to optionally derive and correct for the effect of on-axis leakages of unpolarised ssources to the the other Stokes parameters. The leakages are derived from the bandpass-corrected, spectrally-averaged and flagged PKS1934-638 data. Users need to specify DO_LEAKAGE_CAL_CONT=true to derive the antenna leakages, and specify DO_APPLY_LEAKAGE=true to apply the leakage corrections to uvdata. The leakage correction is applied to gain-corrected data obtained after the self-calibration.

Further imaging : polarisation and cubes

Following this application of the gains and/or leakage calibration solution, one can optionally image the continuum dataset as a cube, preserving the frequency sampling. This task also allows the specification of multiple polarisations, with a cube created for each polarisation given.

A prototype option is available (using DO_MFS_STARTING_MODEL_CONTCUBE) to use the model image from the MFS (continuum) imaging as the starting point for the clean model in the continuum cube imaging.

Following continuum-cube imaging, the cube statistics are calculated, using a distributed task within the same slurm job as the spectral imaging. This produces a file listing a series of statistics for each channel, as well as a plot of the statistics. See Validation and Diagnostics for examples. These statistics are then used to identify problematic channels (for example, due to divergence in the imaging caused by RFI) that are then masked. Blank channels (those not imaged, e.g. due to barycentric correction or missing data) are also masked. The statistics file is then regenerated.

A note on the imagers and the output formats. The default approach is to now use imager (imager) for both continuum and spectral imaging. The use of simager for spectral imaging (in this case, the continuum cubes) is to be discouraged, as imager provides much better functionality for integration into the pipeline. The use of cimager for the MFS imaging is possible, although it provides less flexibility in how the job can be distributed across nodes. The choice of imaging task is governed by DO_ALT_IMAGER_CONT or DO_ALT_IMAGER_CONTCUBE, with the main switch DO_ALT_IMAGER taking precedence.

The default output format is FITS images, although CASA files can be written instead by setting IMAGETYPE_CONT or IMAGETYPE_CONTCUBE to casa (rather than fits).

This version allows continuum imaging of various polarisation products. The self-calibration stage is used for Stokes-I imaging. The calibrated uv-data is then used to make images of other polarisations. Users need to specify the list of polarisation using CONTIMG_POLARISATIONS in their pipeline configuration file. In a later version, we aim to separate the self-calibration from the imaging, so that all pols including Stokes-I are imaged along with the other polarisations.

Basic imaging parameters

This table summarises the fundamental parameters that govern the continuum imaging, and that are used in most of the different types of imaging jobs. This also has specific parameters related to the use of imager.

Variable	Default	Parset equivalent	Description
DO_CONT_IMAGING	true	none	Whether to image the science MS
JOB_TIME_CONT_IMAGE	JOB_TIME_DEFAULT (24:00:00)	none	Time request for imaging the continuum (both types - with and without self-calibration)
IMAGETYPE_CONT	fits	imagetype (cimager and imager)	Image format to use - can be either ‘casa’ or ‘fits’.
IMAGETYPE_CONTCUBE	fits	imagetype (imager)	Image format to use - can be either ‘casa’ or ‘fits’, although ‘fits’ can only be given in conjunction with DO_ALT_IMAGER_CONTCUBE=true.
`MULTI_JOB_SELFCAL	false	none	Whether to break the selfcal up into separate slurm jobs for each imaging and calibration task (true) or whether to combine them all into a single slurm job.
JOB_TIME_CONT_SELFCAL	JOB_TIME_DEFAULT (24:00:00)	none	Time request for the calibration jobs when running with MULTI_JOB_SELFCAL=true.
Basic variables
IMAGE_AT_BEAM_CENTRES	true	none	Whether to have each beam’s image centred at the centre of the beam (IMAGE_AT_BEAM_CENTRES=true), or whether to use a single image centre for all beams.
NUM_CORES_CONTIMG_SCI	""	none	The number of cores in total to use for the continuum imaging. If left blank ("" - the default), then this is calculated based on the number of channels and Taylor terms.
CHANNEL_SELECTION_CONTIMG_SCI	""	Channels (Data Selection)	If NUM_CORES_CONTIMG_SCI is given, the Channels selection is provided here. This can be left blank for no selection to be applied, or a string (in quotes) conforming to the data selection syntax can be provided.
CORES_PER_NODE_CONT_IMAGING	6 (galaxy), 36 (setonix/petrichor)	Not for parset	Number of cores to use on each node in the continuum imaging.
FAT_NODE_CONT_IMG	true	Not for parset	Whether the master process for the continuum imaging should be put on a node of its own (if `true`), or just treated like all other processes.
DATACOLUMN	DATA	datacolumn (cimager)	The column in the measurement set from which to read the visibility data. The default, ‘DATA’, is appropriate for datasets processed within askapsoft, but if you are trying to image data processed, for instance, in CASA, then changing this to CORRECTED_DATA may be what you want.
IMAGE_BASE_CONT	i.%t.SB%s.cont	Helps form Images.Names (cimager)	The base name for images: if IMAGE_BASE_CONT=i.blah then we’ll get image.i.blah, image.i.blah.restored, psf.i.blah etc. The %s wildcard will be resolved into the scheduling block ID and %t will be replaced by the “target” or scheduling block alias.
DIRECTION_SCI	none	Images.<imagename>.direction (cimager)	The direction parameter for the images, i.e. the central position. Can be left out, in which case Cimager will get it from either the beam location (for IMAGE_AT_BEAM_CENTRES=true) or from the measurement set using the “advise” functionality (for IMAGE_AT_BEAM_CENTRES=false).
NUM_PIXELS_CONT	6144	Images.shape (cimager)	The number of pixels on the side of the images to be created. If negative, zero, or absent (i.e. NUM_PIXELS_CONT=""), this will be set automatically by the Cimager “advise” function, based on examination of the MS. Note that this default will be suitable for a single beam, but probably not for an image to be large enough for the full set of beams (when using IMAGE_AT_BEAM_CENTRES=false). The default value, combined with the default for the cell size, should be sufficient to cover a full field. If you have IMAGE_AT_BEAM_CENTRES=true then this needs only to be big enough to fit a single beam.
CELLSIZE_CONT	2	Images.cellsize (cimager)	Size of the pixels in arcsec. If negative, zero or absent, this will be set automatically by the Cimager “advise” function, based on examination of the MS. The default is chosen together with the default number of pixels to cover a typical ASKAP beam with the sidelobes being imaged.
NUM_TAYLOR_TERMS	2	Images.image.${imageBase}.nterms (cimager) linmos.nterms (linmos (Linear Mosaic Applicator))	Number of Taylor terms to create in MFS imaging. If more than 1, MFS weighting will be used (equivalent to setting Cimager.visweights=MFS in the cimager parset).
MFS_REF_FREQ	no default	visweights.MFS.reffreq (cimager)	Frequency at which continuum image is made [Hz]. This is the reference frequency for the multi-frequency synthesis, which should usually be the middle of the band. If negative, zero, or absent (the default), this will be set automatically to the average of the frequencies being processed.
RESTORING_BEAM_CONT	fit	restore.beam (cimager & Solvers)	Restoring beam to use: ‘fit’ will fit the PSF to determine the appropriate beam, else give a size (such as “[30arcsec, 30arcsec, 0deg]”). NB: If PRECONDITIONER_GAUSS_TAPER_IS_PSF=true the restoring beam will be derived such that the output image has the specified resolution.
RESTORING_BEAM_CUTOFF_CONT	0.5	restore.beam.cutoff (simager)	Cutoff value used in determining the support for the fitting (ie. the rectangular area given to the fitting routine). Value is a fraction of the peak.
CIMAGER_MINUV	0	MinUV (Data Selection)	The minimum UV distance considered in the imaging - used to exclude the short baselines. Can be given as an array with different values for each self-cal loop (e.g. "[200,200,0]").
CIMAGER_MAXUV	0	MaxUV (Data Selection)	The maximum UV distance considered in the imaging. Only used if greater than zero. Can be given as an array with different values for each self-cal loop (e.g. "[200,200,0]").
Gridding parameters
GRIDDER	MPIWProject	gridder (Gridders)	Specify griddder to use: WProject or MPIWProject MPIWProject can save memory and time when using multiple ranks
DO_NYQUIST_GRIDDING_CONT	true	Images.nyquistgridding (imager)	Whether to turn on Nyquist gridding.
GRIDDER_SNAPSHOT_IMAGING	false	snapshotimaging (Gridders)	Whether to use snapshot imaging when gridding.
GRIDDER_SNAPSHOT_WTOL	2600	snapshotimaging.wtolerance (Gridders)	The wtolerance parameter controlling how frequently to snapshot.
GRIDDER_SNAPSHOT_LONGTRACK	true	snapshotimaging.longtrack (Gridders)	The longtrack parameter controlling how the best-fit W plane is determined when using snapshots.
GRIDDER_SNAPSHOT_CLIPPING	0.01	snapshotimaging.clipping (Gridders)	If greater than zero, this fraction of the full image width is set to zero. Useful when imaging at high declination as the edges can generate artefacts.
GRIDDER_WMAX	2600 (GRIDDER_SNAPSHOT_IMAGING=true) or 35000 (GRIDDER_SNAPSHOT_IMAGING=false)	MPIWProject.wmax (Gridders)	The wmax parameter for the gridder. The default for this depends on whether snapshot imaging is invoked or not (GRIDDER_SNAPSHOT_IMAGING).
GRIDDER_WMAXCLIP	false	MPIWProject.wmaxclip (Gridders)	The wmaxclip parameter, used for all gridders. By default, a hard cut for w planes on [-wmax,wmax] is made and values outside this range will trigger an error. When true, w values outside this range are ignored.
GRIDDER_NWPLANES	99 (GRIDDER_SNAPSHOT_IMAGING=true) or 999 (GRIDDER_SNAPSHOT_IMAGING=false)	MPIWProject.nwplanes (Gridders)	The nwplanes parameter for the gridder. The default for this depends on whether snapshot imaging is invoked or not (GRIDDER_SNAPSHOT_IMAGING).
GRIDDER_OVERSAMPLE	8	MPIWProject.oversample (Gridders)	The oversampling factor for the gridder.
GRIDDER_MAXSUPPORT	512 (GRIDDER_SNAPSHOT_IMAGING=true) or 3072 (GRIDDER_SNAPSHOT_IMAGING=false)	MPIWProject.maxsupport (Gridders)	The maxsupport parameter for the gridder. The default for this depends on whether snapshot imaging is invoked or not (GRIDDER_SNAPSHOT_IMAGING).
GRIDDER_SHARECF	true	MPIWProject.sharecf (Gridders)	Whether to use a (static) cache for the convolution functions in the WProject gridder.
GRIDDER_CFRANK	16	MPIWProject.cfrank (Gridders)	Number of ranks per node to use to speed up convolution function calculation. Useful range: ~4 to #ranks/node
GRIDDER_SPHFUNC_OFFSETFIELD	false	Cimager.sphfuncforoffset (cimager)	If true, the default spheroidal function gridder is used to grid offset fields regardless of the gridder selected for model degridding and residual gridding.
Preconditioning / weighting parameters
PRECONDITIONER_LIST	"[Wiener]"	preconditioner.Names (Solvers)	List of preconditioners to apply. Can be varied for each selfcal cycle (e.g. "[Wiener] ; [Wiener, GaussianTaper]". Notice the delimiter " ; " and the spaces around it.
PRECONDITIONER_GAUSS_TAPER	"[10arcsec, 10arcsec, 0deg]"	preconditioner.GaussianTaper (Solvers)	Size of the Gaussian taper - either single value (for circular taper) or 3 values giving an elliptical size. Can be varied for each selfcal cycle.
PRECONDITIONER_GAUSS_TAPER_IS_PSF	"false"	preconditioner.GaussianTaper.isPsfSize (Solvers)	Decide if rather than applying the specified taper, the taper should be adjusted to ensure that the output image has the specified resolution. NB: This parameter is also passed to coarse cube imaging. Can be varied for each selfcal cycle.
PRECONDITIONER_GAUSS_TAPER_TOL	0.005	preconditioner.GaussianTaper.tolerance (Solvers)	Fractional tolerance for the fitted beam size when PRECONDITIONER_GAUSS_TAPER_IS_PSF = true The default is set to 0.5% Can be varied for each selfcal cycle.
PRECONDITIONER_WIENER_ROBUSTNESS	-0.5	preconditioner.Wiener.robustness (Solvers)	Robustness value for the Wiener filter. Can be varied for each selfcal cycle.
PRECONDITIONER_WIENER_TAPER	""	preconditioner.Wiener.taper (Solvers)	Size of gaussian taper applied in image domain to Wiener filter. Ignored if blank (ie. “”). Can be varied for each selfcal cycle.
RESTORE_PRECONDITIONER_LIST	""	restore.preconditioner.Names (cimager & Solvers)	List of preconditioners to apply at the restore stage, to produce an additional restored image.
RESTORE_PRECONDITIONER_EXTENSION	alt	restore.preconditioner.suffix (cimager & Solvers)	The additional suffix or extension added to the image name for the additional restored images with alternate preconditioning.
RESTORE_PRECONDITIONER_GAUSS_TAPER	"[10arcsec, 10arcsec, 0deg]"	restore.preconditioner.GaussianTaper (cimager & Solvers)	Size of the Gaussian taper for the restore preconditioning - either single value (for circular taper) or 3 values giving an elliptical size.
RESTORE_PRECONDITIONER_GAUSS_TAPER_IS_PSF	"false"	preconditioner.GaussianTaper.isPsfSize (Solvers)	Decide if rather than applying the specified taper for images restored with alternate preconditioning, the taper should be adjusted to ensure that the output image has the specified resolution.
RESTORE_PRECONDITIONER_GAUSS_TAPER_TOL	0.005	preconditioner.GaussianTaper.tolerance (Solvers)	Fractional tolerance for the fitted beam size when RESTORE_PRECONDITIONER_GAUSS_TAPER_IS_PSF = true The default is set to 0.5%
RESTORE_PRECONDITIONER_WIENER_ROBUSTNESS	-2	restore.preconditioner.Wiener.robustness (cimager & Solvers)	Robustness value for the Wiener filter in the restore preconditioning.
RESTORE_PRECONDITIONER_WIENER_TAPER	""	restore.preconditioner.Wiener.taper (cimager & Solvers)	Size of gaussian taper applied in image domain to Wiener filter in the restore preconditioning. Ignored if blank (ie. “”).
TRADITIONAL_WEIGHT_PARAM_LIST	""	uvweight (imager)	List of parameters for application of traditional weights.
TRADITIONAL_WEIGHT_ROBUSTNESS	-0.5	uvweight.robustness (imager)	The value of robustness. Only used if there is Robust among the list of parameters given by TRADITIONAL_WEIGHT_PARAM_LIST.
*New imager parameters
DO_ALT_IMAGER_CONT	""	none	If true, the continuum imaging is done by imager (imager). If false, it is done by cimager (cimager). If left blank (the default), the value is given by the overall parameter DO_ALT_IMAGER (see User Parameters - Pipeline & job control).

Self-calibration

This table summarises the parameters related to stokes-I imaging and the self-calibration procedure. The Stokes I imaging gets its own set of deconvolution (cleaning) parameters (the Stokes I images will be made in the self-cal part, not the “contpol” part of the pipeline). There are parameters related to the source-finding and calibration parts of the self-calibration

Variable	Default	Parset equivalent	Description
Cleaning parameters
SOLVER	Clean	solver (cimager) (Solvers)	Which solver to use. You will mostly want to leave this as ‘Clean’, but there is a ‘Dirty’ solver available.
CLEAN_ALGORITHM	BasisfunctionMFS	Clean.algorithm (Solvers)	The name(s) of clean algorithm(s) to use. To use different algorithms in different selfcal cycles, use: CLEAN_ALGORITHM="Hogbom,BasisfunctionMFS" If the number of comma-separated algorithms is less than SELFCAL_NUM_LOOPS + 1, the first algorithm specified will be used for ALL selfcal loops.
CLEAN_MINORCYCLE_NITER	"[400,800]"	Clean.niter (Solvers)	The number of iterations for the minor cycle clean. Can be varied for each selfcal cycle. (e.g. "[200,800,1000]")
CLEAN_GAIN	0.2	Clean.gain (Solvers)	The loop gain (fraction of peak subtracted per minor cycle). Can be varied for each selfcal cycle. (e.g. "[0.1,0.2,0.1]")
CLEAN_PSFWIDTH	256	Clean.psfwidth (Solvers)	The width of the psf patch used in the minor cycle. Can be varied for each selfcal cycle. (e.g. "[256,512,4096]")
CLEAN_SCALES	"[0,3,10]"	Clean.scales (Solvers)	Set of scales (in pixels) to use with the multi-scale clean. Can be varied for each selfcal cycle (e.g. "[0] ; [0,10]") Notice the delimiter " ; " and the spaces around it.
CLEAN_POSITIVITY	"[false,false,false]"	Clean.positivity (Solvers)	Whether each scale used should be constrained to be positive only.
CLEAN_THRESHOLD_MINORCYCLE	"[30%, 5.0sigma, 0.5sigma]"	threshold.minorcycle (cimager) (Solvers)	Threshold for the minor cycle loop. Can be varied for each selfcal cycle. (e.g. "[30%,1.8mJy,0.03mJy] ; [20%,0.5mJy,0.03mJy]") Notice the delimiter " ; " and the spaces around it.
CLEAN_THRESHOLD_MAJORCYCLE	"0.035mJy"	threshold.majorcycle (cimager) (Solvers)	The target peak residual. Major cycles stop if this is reached. A negative number ensures all major cycles requested are done. Can be given as an array with different values for each self-cal loop (e.g. "[3mJy,1mJy,-1mJy]").
CLEAN_NUM_MAJORCYCLES	"[5,10]"	ncycles (cimager)	Number of major cycles. Can be given as an array with different values for each self-cal loop (e.g. "[2,4,6]").
CLEAN_WRITE_AT_MAJOR_CYCLE	false	Images.writeAtMajorCycle (cimager)	If true, the intermediate images will be written (with a .cycle suffix) after the end of each major cycle.
CLEAN_SOLUTIONTYPE	MAXBASE	Clean.solutiontype (see discussion at Multi-Scale and/or Multi-Frequency deconvolution)	The type of peak finding algorithm to use in the deconvolution. Choices are MAXCHISQ, MAXTERM0, or MAXBASE.
CLEAN_DETECT_DIVERGENCE	true	Clean.detectdivergence (Solvers)	Whether to detect that the deconvolution is starting to diverge (in which case it is stopped).
CLEAN_DETECT_MILD_DIVERGENCE	true	Clean.detectmilddivergence (Solvers)	Whether to use the mild form of divergence detection, that should skip to the next major cycle if residuals increase by 10% or more.
CLEAN_DIVERGENCE_PARAMETERS	“[1.1,2.0,2.0,0.05]”	Clean.divergencelevels (Solvers)	Setting the levels for divergence detection to be used in the continuum imaging.
CLEAN_NOISEBOXSIZE	0	Clean.noiseboxsize (Solvers)	Size of the box used to determine the local noise value for setting thresholds (when a “sigma” threshold is given). A value of 0 means the entire image is used.
CLEAN_MASK	false	Clean.usemask (Solvers)	Set to true if we are using a clean mask image - consult Solvers for details on image name and content.
Self-calibration - basics
DO_SELFCAL	true	none	Whether to self-calibrate the science data when imaging.
USE_SELFCAL_LOOP_INDEX	0	none	When DO_SELFCAL=false, use this index into the loop-dependent parameter arrays for the Stokes I imaging.
EXTERNAL_CATALOGUE	""	NONE	If provided, this catalogue is used to generate a model that is then used to provide phase-only calibration prior to the first round of imaging. Special values of this are “racs_mid” or “racs_low”, to search those whole-sky catalogues through the online Sky Model Service interface in cmodel.
SELFCAL_METHOD	Cmodel	none	How to do the self-calibration. There are three options: “Cmodel” means create a model image from the source-finding results; “Components” means use the detected components directly through a parset (created by Selavy); “CleanModel” means use the clean model image from the most recent imaging as the model for ccalibrator. Anything else will default to “Cmodel”.
CMODEL_NEAREST_SELFCAL	true	Cmodel.nearest (cmodel)	For SELFCAL_METHOD=Cmodel, whether to use nearest neighbour interpolation for point sources. If set to false, Lanczos5 interpolation will be used.
SELFCAL_SOLVER	SVD	solver (Calibration solvers)	Selection of solver - either “SVD” or “LSQR”
SELFCAL_ALPHA	0.01	solver (Calibration solvers)	Damping parameter for “LSQR” solver. Ignored for SVD.
SELFCAL_NUM_LOOPS	1	none	Number of loops of self-calibration.
SELFCAL_INTERVAL	"[200,200]"	interval (ccalibrator)	Interval [sec] over which to solve for self-calibration. Can be given as an array with different values for each self-cal loop, as for the default, or a single value that applies to each loop.
GAINS_CAL_TABLE	calparameters.selfcal.%t.SB%s.%b.tab	none (directly)	The table name to hold the final gains solution. Once the self-cal loops have completed, the cal table in the final loop is copied to a table of this name in the base directory. This can then be used for the spectral-line imaging if need be. If this is blank, both DO_SELFCAL and DO_APPLY_CAL_SL will be set to false. The %s wildcard will be resolved into the scehduling block ID, %t will be replaced with the “target”, or scheduling block alise, and the %b will be replaced with “FIELD_beamBB”, where FIELD is the field id, and BB the (zero-based) beam number.
SELFCAL_NORMALISE_GAINS	true	normalisegains (ccalibrator)	Whether to normalise the amplitudes of the gains to 1, approximating the phase-only self-calibration approach. Can be given as an array with different values for each self-cal loop (e.g. “[true,true,false]”).
DO_INTERPOLATE_SELFCAL_GAINS	false	calibrate.interpolatetime (imager, cimager and ccalapply (Calibration Applicator))	Whether to interpolate the self-cal gains (amp and pha). If true, interpolated solutions will be used for the interim imaging within the selfcal loops, and in the final stages of calibration application to the continuum and spectral-line measurement sets used for the respective cube imaging. Only linear interpolation is allowed.
SELFCAL_REF_ANTENNA	""	refantenna (ccalibrator)	Reference antenna to use in the calibration. Should be antenna number, 0 - nAnt-1, that matches the antenna numbering in the MS.
SELFCAL_REF_GAINS	""	refgains (ccalibrator)	Reference gains to use in the calibration - something like gain.g11.0.0.
SELFCAL_SCALENOISE	false	calibrate.scalenoise (cimager)	Whether the noise estimate will be scaled in accordance with the applied calibrator factor to achieve proper weighting.
CCALIBRATOR_MINUV	0	MinUV (Data Selection)	The minimum UV distance considered in the calibration - used to exclude the short baselines. Can be given as an array with different values for each self-cal loop (e.g. "[200,200,0]").
CCALIBRATOR_MAXUV	0	MaxUV (Data Selection)	The maximum UV distance considered in the calibration. Only used if greater than zero. Can be given as an array with different values for each self-cal loop (e.g. "[200,200,0]").
SELFCAL_KEEP_IMAGES	true	none	Should we keep the images from the intermediate selfcal loops?
MOSAIC_SELFCAL_LOOPS	false	none	Should we make full-field mosaics for each loop of the self-calibration? This is done for each field separately.
SELFCAL_MASK_FROM_RESTORED_IMAGE	true	none	If true, use the restored image for mask generation. May work well for the “adaptive” strategy.
SELFCAL_MASK_CLEAN_MODEL	false	none	If true, a copy of the clean model image is made to be used for calibration, and it is then masked to remove pixels below a certain threshold - to avoid negative or weak components.
SELFCAL_MASK_STRATEGY	threshold	none	Which method to use for the masking. Options are “threshold” or “adaptive”.
SELFCAL_MASK_CLEAN_MODEL_THRESHOLD	0.0	none	The threshold below which pixels are masked in the modified clean model image. Units are given by the next parameter.
SELFCAL_MASK_CLEAN_MODEL_THRESHOLD_TYPE	absolute	none	The units of the threshold: ‘absolute’ means the native image flux values (typically Jy/pixel); ‘sigmaBased’ means the threshold is in multiples of the image noise.
SELFCAL_MASK_ADAPTIVE_GAUSSWIDTH	32	none	Width of the Gaussian kernel (in pixel units). Larger values detect broader (background) features.
SELFCAL_MASK_ADAPTIVE_THRESHOLD	1.0	none	The detection threshold, in units of sigma.
SELFCAL_MASK_ADAPTIVE_KERNEL_SIZE	5.0	none	Size of Gaussian kernel in units of width of the Gaussian: SELFCAL_MASK_ADAPTIVE_GAUSSWIDTH
SELFCAL_MASK_ADAPTIVE_MINFLUX	0.0	none	Minimum value (Jy) threshold - all pixels below this value will be masked.
Self-calibration - source-finding
SELFCAL_SELAVY_THRESHOLD	8	snrCut (Selavy Basics)	SNR threshold for detection with Selavy in determining selfcal sources. Can be given as an array with different values for each self-cal loop (e.g. "[15,10,8]").
SELFCAL_SELAVY_NSUBX	6	nsubx (Selavy Basics)	Division of image in x-direction for source-finding in selfcal.
SELFCAL_SELAVY_NSUBY	3	nsuby (Selavy Basics)	Division of image in y-direction for source-finding in selfcal.
SELFCAL_SELAVY_GAUSSIANS_FROM_GUESS	true	Selavy.Fitter.numGaussFromGuess (Post-processing of detections)	Whether to fit the number of Gaussians given by the initial estimate (true), or to only fit a fixed number (false). The number is given by SELFCAL_SELAVY_NUM_GAUSSIANS.
SELFCAL_SELAVY_NUM_GAUSSIANS	1	Selavy.Fitter.maxNumGauss (Post-processing of detections)	The number of Gaussians to fit to each island when SELFCAL_SELAVY_GAUSSIANS_FROM_GUESS=false.
SELFCAL_SELAVY_FIT_TYPE	full	Selavy.Fitter.fitTypes (Post-processing of detections)	The type of fit to be used in the Selavy job. The possible options are ‘full’, ‘psf’, ‘shape’, or ‘height’.
SELFCAL_SELAVY_WEIGHTSCUT	0.95	Selavy.Weights.weightsCutoff (Thresholds in Selavy)	Pixels with weight less than this fraction of the peak weight will not be considered by the source-finding. If the value is negative, or more than one, no consideration of the weight is made.
SELFCAL_SELAVY_SPECTRAL_INDEX_THRESHOLD	“”	spectralTerms.threshold (Post-processing of detections)	Threshold applied to component peak fluxes in determining which have a spectral index (and curvature) value reported in the component catalogue. Not used if left blank. Takes precedence over SELFCAL_SELAVY_SPECTRAL_INDEX_THRESHOLD_SNR.
SELFCAL_SELAVY_SPECTRAL_INDEX_THRESHOLD_SNR		spectralTerms.thresholdSNR (Post-processing of detections)	Threshold applied to component peak signal-to-noise values in determining which have a spectral index (and curvature) value reported in the component catalogue. Not used if left blank.
SELFCAL_COMPONENT_SNR_LIMIT	10	Used to create Cmodel.flux_limit (cmodel)	The signal-to-noise level used to set the flux limit for components that are used by Cmodel. The image noise values reported for all components are averaged, then multiplied by this value to form the Cmodel flux limit. If left blank (""), the flux limit is determined by SELFCAL_MODEL_FLUX_LIMIT.
SELFCAL_MODEL_FLUX_LIMIT	10uJy	Cmodel.flux_limit (cmodel)	The minimum integrated flux for components to be included in the model used for self-calibration.
DO_POSITION_OFFSET	false	none	Whether to add a fixed RA & Dec offset to the positions of sources in the final self-calibration catalogue (prior to it being used to calibrate the data). This has been implemented to help with commissioning - do not use unless you understand what it is doing! This makes use of the script legacy/fix_position_offsets.py.
RA_POSITION_OFFSET	0	none	The offset in position in the RA direction, in arcsec. This is taken from the offset_pipeline_params.txt file produced by the continuum validation script, where the sense of the offset is REFERENCE-ASKAP.
DEC_POSITION_OFFSET	0	none	The offset in position in the DEC direction, in arcsec. This is taken from the offset_pipeline_params.txt file produced by the continuum validation script, where the sense of the offset is REFERENCE-ASKAP.

Applying the gains and leakage calibration

This table shows the parameters relevant to the jobs that apply the self-cal gains to the averaged dataset, and then the leakages to the gain-refined measurement sets. This is done before the continuum-polarisation imaging and the continuum-cube imaging.

Variable	Default	Parset equivalent	Description
Application of gains calibration
DO_APPLY_CAL_CONT	true	none	Whether to apply the calibration to the averaged (“continuum”) dataset.
JOB_TIME_CONT_APPLYCAL	JOB_TIME_DEFAULT (24:00:00)	none	Time request for applying the calibration
KEEP_RAW_AV_MS	true	none	Whether to make a copy of the averaged MS before applying the gains calibration (true), or to just overwrite with the calibrated data (false).
DO_APPLY_LEAKAGE	false	none	Whether to apply the leakage calibration to the averaged and self-calibrated (“continuum”) dataset derived using: DO_LEAKAGE_CAL_CONT=true

Additionally, instrumental leakage of Stokes-I into other Stokes parameters in off-axis regions of the beams can be corrected during mosaicking. For more details, see the pipeline documentation on linear mosaicking at User Parameters - Mosaicking and code documentation at linmos (Linear Mosaic Applicator).

Continuum Polarisation imaging

Once the gains have been applied and/or leakages have been corrected, MFS imaging may be done in a selected set of polarisations - use DO_CONTPOL_IMAGING=true to turn this mode on.

If “I” is given as one of them, it is not re-imaged, as we have an image from the self-calibration routine. The cleaning parameters are given separately here (as thresholds may need to be different), although gridding and preconditioning are assumed to be the same. Many of these parameters can be given as arrays, with different values for each polarisation. If a single value is given, that applies to all polarisations.

Variable	Default	Parset equivalent	Description
Imaging parameters
DO_CONTPOL_IMAGING	false	none	Whether to create continuum polarisation images
CONTIMG_POLARISATIONS	"I,V"	ImageName.polarisation (cimager)	Comma separated list of Polarisations to be imaged Stokes-I is ignored here, since it is imaged in the self-cal loop
CIMAGER_CONTPOL_MINUV	0	MinUV (Data Selection)	The minimum UV distance considered in the imaging - used to exclude the short baselines. Can be given as an array with different values for each pol loop (e.g. "[200,200,0]").
CIMAGER_CONTPOL_MAXUV	0	MaxUV (Data Selection)	The maximum UV distance considered in the imaging. Only used if greater than zero. Can be given as an array with different values for each pol loop (e.g. "[200,200,0]").
Cleaning parameters
CLEAN_CONTPOL_ALGORITHM	BasisfunctionMFS	Clean.algorithm (Solvers)	The name(s) of clean algorithm(s) to use. To use different algorithms in different selfcal cycles, use: CLEAN_CONTPOL_ALGORITHM="Hogbom,BasisfunctionMFS" If the number of comma-separated algorithms is less than the number of pol specified, the first algorithm specified will be used for ALL pol loops.
CLEAN_CONTPOL_MINORCYCLE_NITER	"800"	Clean.niter (Solvers)	The number of iterations for the minor cycle clean. Can be varied for each pol. (e.g. "[200,800,1000]")
CLEAN_CONTPOL_GAIN	0.2	Clean.gain (Solvers)	The loop gain (fraction of peak subtracted per minor cycle). Can be varied for each pol cycle. (e.g. "[0.1,0.2,0.1]")
CLEAN_CONTPOL_PSFWIDTH	256	Clean.psfwidth (Solvers)	The width of the psf patch used in the minor cycle. Can be varied for each pol (e.g. "[256,512,4096]")
CLEAN_CONTPOL_SCALES	"[0,3,10]"	Clean.scales (Solvers)	Set of scales (in pixels) to use with the multi-scale clean. Can be varied for each specified polarisation (e.g. "[0] ; [0,10]") Notice the delimiter " ; " and the spaces around it.
CLEAN_CONTPOL_POSITIVITY	"[false,false,false]"	Clean.positivity (Solvers)	Whether each scale used should be constrained to be positive only.
CLEAN_CONTPOL_THRESHOLD_MINORCYCLE	"[30%, 5.0sigma, 0.5sigma]"	threshold.minorcycle (cimager) (Solvers)	Threshold for the minor cycle loop. Can be varied for each polarisation. (e.g. "[30%,1.8mJy,0.03mJy] ; [20%,0.5mJy,0.03mJy]") Notice the delimiter " ; " and the spaces around it.
CLEAN_CONTPOL_THRESHOLD_MAJORCYCLE	"0.035mJy"	threshold.majorcycle (cimager) (Solvers)	The target peak residual. Major cycles stop if this is reached. A negative number ensures all major cycles requested are done. Can be given as an array with different values for each pol loop (e.g. "[3mJy,1mJy,-1mJy]").
CLEAN_CONTPOL_NUM_MAJORCYCLES	"3"	ncycles (cimager)	Number of major cycles. Can be given as an array with different values for each pol loop (e.g. "[2,4,6]").
CLEAN_CONTPOL_WRITE_AT_MAJOR_CYCLE	false	Images.writeAtMajorCycle (cimager)	If true, the intermediate images will be written (with a .cycle suffix) after the end of each major cycle.
CLEAN_CONTPOL_SOLUTIONTYPE	MAXBASE	Clean.solutiontype (see discussion at Multi-Scale and/or Multi-Frequency deconvolution)	The type of peak finding algorithm to use in the deconvolution. Choices are MAXCHISQ, MAXTERM0, or MAXBASE.
CLEAN_CONTPOL_READ_SCALEMASK	""	Clean.readscalemask (Solvers)	If not blank, this is the name of the scalemask image. This functionality needs further development and so users should use this at their own risk!
CLEAN_CONTPOL_SCALEMASK_I_ONLY	true	none	If true, only read the scale mask for Stokes I imaging. If false, it is read for all Stokes images.
CLEAN_CONTPOL_NOISEBOXSIZE	0	Clean.noiseboxsize(Solvers)	Size of the box used to determine the local noise value for setting thresholds (when a “sigma” threshold is given). A value of 0 means the entire image is used.
CLEAN_CONTPOL_MASK	false	Clean.usemask (Solvers)	Set to true if we are using a clean mask image - consult Solvers for details on image name and content.

Optional Image products

Imager allows users to specify whether or not to write optional output products such as the residual, weights, natural psf, preconditioned psf etc. images. These are aimed at minimising disk I/O and occupancy where possible.

Note that information on weights is required by the linear mosaicking applications: linmos and linmos-mpi. For non A-Projection gridders like WProject, where the weights value across the image extent is constant, imager can write out the weight value into an ascii text file that linmos can make use of. This can be specified using WRITE_WEIGHTS_LOG_CONT parameter for the continuum imaging case.

For A-project gridders, or when snapshot imaging is turned on, one will have to necessarily write out the weights images for use in linmos. An exception will be thrown by processASKAP.sh if this condition is violated.

More details on writing these optional image products are discussed in the sections for continuum and continuum cube imaging below. See also User Parameters - Spectral-line Imaging and User Parameters - Mosaicking.

Variable	Default	Parset equivalent	Description
Optional outputs
WRITE_RESIDUAL_CONT	true	write.residualimage (imager)	Whether to write the residual image
WRITE_PSF_RAW_CONT	false	write.psfrawimage (imager)	Whether to write the naturally weighted psf image
WRITE_PSF_IMAGE_CONT	false	write.psfimage (imager)	Whether to write the preconditioned psf image
WRITE_WEIGHTS_IMAGE_CONT	false	write.weightsimage (imager)	Whether to write the weights image
WRITE_WEIGHTS_LOG_CONT	true	write.weightslog (imager)	Option to write the constant weight into an ascii text file Note 1: Should not be used with A-project gridders. Note 2: For snapshot imaging, this option is internally forced to “false” by the pipeline scripts. Set WRITE_WEIGHTS_IMAGE_CONT=true in this case.
WRITE_MODEL_IMAGE_CONT	true	write.modelimage (imager)	Whether to write the model image Note: The pipeline ensures that intermediate model images get generated if required by selfcal jobs.
WRITE_MASK_IMAGE_CONT	false	write.maskimage (imager)	Whether to write the mask image (continuum only)
WRITE_SCALEMASK_IMAGE_CONT	false	write.scalemask (imager)	Whether to write the scalemask image (continuum only)
WRITE_SENSITIVITY_IMAGE_CONT	false	write.sensitivityimage (imager)	Whether to write sensitivity image (continuum only)
WRITE_FIRST_RESTORE_CONT	true	write.firstrestore (imager)	Whether to write the first restored image when alt-restored images are requested (continuum only)

Continuum cube imaging

Once the gains have been applied to the averaged dataset, it can be imaged as “continuum cubes” in a variety of polarisations - use DO_CONTCUBE_IMAGING=true to turn this mode on.

This table lists all relevant parameters that are different to the MFS imaging. Some parameters, notably gridding and preconditioning, are the same. There are also parameters related to the use of imager.

Variable	Default	Parset equivalent	Description
Imaging parameters
DO_CONTCUBE_IMAGING	false	none	Whether to create continuum cubes
JOB_TIME_CONTCUBE_IMAGE	JOB_TIME_DEFAULT (24:00:00)	none	Time request for individual continuum cube jobs
IMAGE_BASE_CONTCUBE	i.%t.SB%s.contcube	Helps form Images.name (imager)	Base name for the continuum cubes. It should include “i.”, as the actual base name will include the correct polarisation (‘I’ will produce i.contcube, Q will produce q.contcube and so on). The %s wildcard will be resolved into the scheduling block ID, and %t will be replaced by the “target” or scheduling block alias.
NUM_PIXELS_CONTCUBE	4096	Images.shape (imager)	Number of pixels on the spatial dimension for the continuum cubes.
CELLSIZE_CONTCUBE	""	Images.cellsize (imager)	Angular size of spatial pixels for the continuum cubes. If not provided, it defaults to the value of CELLSIZE_CONT
CONTCUBE_POLARISATIONS	"I"	Images.polarisation (imager)	List of polarisations to create cubes for. This should be a comma-separated list of (upper-case) polarisations. Separate jobs will be launched for each polarisation given.
REST_FREQUENCY_CONTCUBE	""	Images.restFrequency (imager)	Rest frequency to be written to the continuum cube. If left blank, no rest frequency is written.
CONTCUBE_IMAGE_MAXUV	0	MaxUV (Data Selection)	A maximum UV distance (in metres) to apply in the data selection step. Only used if a positive value is applied.
CONTCUBE_IMAGE_MINUV	0	MinUV (Data Selection)	A minimum UV distance (in metres) to apply in the data selection step. Only used if a positive value is applied.
DO_NYQUIST_GRIDDING_CONTCUBE	true	Images.nyquistgridding (imager)	Whether to turn on Nyquist gridding.
RESTORING_BEAM_CONTCUBE	fit	restore.beam (imager & Solvers)	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, 30arcsec, 0deg]”). NB: If PRECONDITIONER_GAUSS_TAPER_IS_PSF=true the restoring beams will be derived such that the output image planes have the fixed specified resolution.
RESTORING_BEAM_CUTOFF_CONTCUBE	0.5	restore.beam.cutoff (imager)	Cutoff value used in determining the support for the fitting (ie. the rectangular area given to the fitting routine). Value is a fraction of the peak.
RESTORING_BEAM_CONTCUBE_REFERENCE	mid	restore.beamReference (imager)	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’
NUM_CORES_CONTCUBE_SCI	""	none	Total number of cores to use for the continuum cube job. If left blank, this will be chosen to match the number of channels (taking into account NCHAN_PER_CORE_CONTCUBE if necessary), plus an additional core for the master process.
NCHAN_PER_CORE_CONTCUBE	3 (galaxy), 4 (petrichor), 6 (setonix)	nchanpercore (imager)	If imager (imager) is used, this determines how many channels each worker will process.
CORES_PER_NODE_CONTCUBE_IMAGING	8 (galaxy), 48 (petrichor), 73 (setonix)	none	How many of the cores on each node to use.
Preconditioning
PRECONDITIONER_LIST_CONTCUBE	""	preconditioner.Names (Solvers)	List of preconditioners to apply. If left blank, the preconditioning used for the continuum imaging is used instead, and any values given in the config file for the subsequent parameters are ignored.
PRECONDITIONER_CONTCUBE_GAUSS_TAPER	"[10arcsec, 10arcsec, 0deg]"	preconditioner.GaussianTaper (Solvers)	Size of the Gaussian taper - either single value (for circular taper) or 3 values giving an elliptical size.
PRECONDITIONER_CONTCUBE_GAUSS_TAPER_IS_PSF	"false"	preconditioner.GaussianTaper.isPsfSize (Solvers)	Decide if rather than applying the specified taper, the taper should be adjusted to ensure that the output image planes have the specified resolution.
PRECONDITIONER_CONTCUBE_GAUSS_TAPER_TOL	0.005	preconditioner.GaussianTaper.tolerance (Solvers)	Fractional tolerance for the fitted beam size when PRECONDITIONER_CONTCUBE_GAUSS_TAPER_IS_PSF = true The default is set to 0.5%
PRECONDITIONER_CONTCUBE_WIENER_ROBUSTNESS	-0.5	preconditioner.Wiener.robustness (Solvers)	Robustness value for the Wiener filter.
PRECONDITIONER_CONTCUBE_WIENER_TAPER	""	preconditioner.Wiener.taper (Solvers)	Size of gaussian taper applied in image domain to Wiener filter. Ignored if blank (ie. "").
TRADITIONAL_WEIGHT_PARAM_CONTCUBE_LIST	""	uvweight (imager)	List of parameters for application of traditional weights.
TRADITIONAL_WEIGHT_CONTCUBE_ROBUSTNESS	-0.5	uvweight.robustness (imager)	The value of robustness. Only used if there is Robust among the list of parameters given by TRADITIONAL_WEIGHT_PARAM_CONTCUBE_LIST.
Continuum cube cleaning			Different cleaning parameters used for the continuum cubes
SOLVER_CONTCUBE	Clean	solver (imager) (Solvers)	Which solver to use. You will mostly want to leave this as ‘Clean’, but there is a ‘Dirty’ solver available.
CLEAN_CONTCUBE_ALGORITHM	BasisfunctionMFS	Clean.algorithm (Solvers)	The name of the clean algorithm to use.
DO_MFS_STARTING_MODEL_CONTCUBE	false	none	Whether to use the MFS model image as the starting point for the cleaning of the continuum cube.
CLEAN_CONTCUBE_MINORCYCLE_NITER	600	Clean.niter (Solvers)	The number of iterations for the minor cycle clean.
CLEAN_CONTCUBE_GAIN	0.2	Clean.gain (Solvers)	The loop gain (fraction of peak subtracted per minor cycle).
CLEAN_CONTCUBE_PSFWIDTH	256	Clean.psfwidth (Solvers)	The width of the psf patch used in the minor cycle.
CLEAN_CONTCUBE_SCALES	"[0,3,10]"	Clean.scales (Solvers)	Set of scales (in pixels) to use with the multi-scale clean.
CLEAN_CONTCUBE_POSITIVITY	"[false,false,false]"	Clean.positivity (Solvers)	Whether each scale used should be constrained to be positive only.
CLEAN_CONTCUBE_THRESHOLD_MINORCYCLE	"[40%, 5.0sigma, 0.5sigma]"	threshold.minorcycle (Solvers)	Threshold for the minor cycle loop.
CLEAN_CONTCUBE_THRESHOLD_MAJORCYCLE	0.06mJy	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_CONTCUBE_NUM_MAJORCYCLES	3	ncycles (imager)	Number of major cycles.
CLEAN_CONTCUBE_WRITE_AT_MAJOR_CYCLE	false	Images.writeAtMajorCycle (imager)	If true, the intermediate images will be written (with a .cycle suffix) after the end of each major cycle.
CLEAN_CONTCUBE_SOLUTIONTYPE	MAXBASE	Clean.solutiontype (see discussion at Multi-Scale and/or Multi-Frequency deconvolution)	The type of peak finding algorithm to use in the deconvolution. Choices are MAXCHISQ, MAXTERM0, or MAXBASE.
CLEAN_CONTCUBE_DETECT_DIVERGENCE	true	Clean.detectdivergence (Solvers)	Whether to detect that the deconvolution is starting to diverge (in which case it is stopped).
CLEAN_CONTCUBE_DETECT_MILD_DIVERGENCE	true	Clean.detectmilddivergence (Solvers)	Whether to use the mild form of divergence detection, that should skip to the next major cycle if residuals increase by 10% or more.
CLEAN_CONTCUBE_DIVERGENCE_PARAMETERS	“[1.1,2.0,2.0,0.05]”	Clean.divergencelevels (Solvers)	Setting the levels for divergence detection to be used in the continuum-cube imaging.
CLEAN_CONTCUBE_NOISEBOXSIZE	0	Clean.noiseboxsize(Solvers)	Size of the box used to determine the local noise value for setting thresholds (when a “sigma” threshold is given). A value of 0 means the entire image is used.
CLEAN_CONTCUBE_MASK	false	Clean.usemask (Solvers)	Set to true if we are using a clean mask image - consult Solvers for details on image name and content.
CLEAN_CONTCUBE_READ_SCALEMASK	""	Clean.readscalemask (Solvers)	If not blank, this is the name of the scalemask image. This functionality needs further development and so users should use this at their own risk!
CLEAN_CONTCUBE_SCALEMASK_I_ONLY	true	none	If true, only read the scale mask for Stokes I imaging. If false, it is read for all Stokes contcubes.
New imager parameters
DO_ALT_IMAGER_CONTCUBE	""	none	If true, the continuum cube imaging is done by imager (imager). If false, it is done by cimager (cimager). When true, the following parameters are used. If left blank (the default), the value is given by the overall parameter DO_ALT_IMAGER.
NCHAN_PER_CORE	12 (galaxy/petrichor), 24 (setonix)	nchanpercore (imager)	The number of channels each core will process.
NUM_SPECTRAL_WRITERS_CONTCUBE	""	nwriters (imager)	The number of writers used by imager. Unless ALT_IMAGER_SINGLE_FILE_CONTCUBE=true, this will equate to the number of distinct spectral cubes produced.In the case of multiple cubes, each will be a sub-band of the full bandwidth. No combination of the sub-cubes is currently done. The number of writers will be reduced to the number of workers in the job if necessary. If a single image is produced, the default is to have the same number of writers as workers.
ALT_IMAGER_SINGLE_FILE_CONTCUBE	true	singleoutputfile (imager)	Whether to write a single cube, even with multiple writers (ie. NUM_SPECTRAL_WRITERS_CONTCUBE>1). Only works when IMAGETYPE_SPECTRAL=fits
DO_MASK_BAD_CHANNELS	true	none	Whether to mask out bad or blank channels from the continuum
MASK_CHANS_USE_SIG	false	none	Whether to use the “signifcance”, or the ratio of the 1-percent statistic to the MADFM, to determine the bad channels.
MASK_CHANS_SIG_THRESHOLD		none	The significance level at which to reject channels.
MASK_CHANS_USE_NOISE	true	none	Whether to mask out bad channels on the basis of the MADFM value alone.
MASK_CHANS_NOISE_THRESHOLD		none	The value of MADFM (in mJy/beam), above which a channel is deemed bad.
MASK_CHANS_BLANK	true	none	Whether to mask out blank channels from the continuum cube.
Optional outputs
WRITE_RESIDUAL_CONTCUBE	true	write.residualimage (imager)	Whether to write the residual image cube
WRITE_PSF_RAW_CONTCUBE	false	write.psfrawimage (imager)	Whether to write the naturally weighted psf image cube
WRITE_PSF_IMAGE_CONTCUBE	false	write.psfimage (imager)	Whether to write the preconditioned psf image cube
WRITE_WEIGHTS_IMAGE_CONTCUBE	false	write.weightsimage (imager)	Whether to write the weights image cube
WRITE_WEIGHTS_LOG_CONTCUBE	true	write.weightslog (imager)	Option to write the weight spectra into an ascii text file Note 1: Should not be used with A-project gridders. Note 2: For snapshot imaging, this option is internally forced to “false” by the pipeline scripts. Set WRITE_WEIGHTS_IMAGE_CONT=true in this case.
WRITE_MODEL_IMAGE_CONTCUBE	true	write.modelimage (imager)	Whether to write the model image cube Note: The pipeline ensures that intermediate model images get generated if required by selfcal jobs.
WRITE_UVGRIDS_CONTCUBE	false	write.grids (imager)	Whether to write the UV-grids (cubes only)

Fast / Transient imaging

The pipeline presents a transient-imaging workflow, where continuum images are made over intervals shorter than the total observation time. The workflow is summarised as follows:

• For a given beam dataset, the deep continuum clean model (from the full continuum imaging) is subtracted using ccontsubtract, to create a coarse-resolution continuum-subtracted MS.

• This MS is imaged sequentially in each of a number of time intervals spanning the full observation duration:

  • The intervals are calculated by the python script transientIntervals.py. This takes a nominated interval length (TRANSIENT_INTERVAL, in seconds), and adjusts it to be a whole number of integrations.

  • A series of start and end times are then calculated, which are presented to imager via the parset parameter Cimager.TimeRange (see imager).

  • Each interval is then imaged in sequence, producing a single restored image for each interval.

• These images are then given to the Vaster module, a containerised set of scripts provided by the VAST Survey Science Team, to perform transient detection. This uses the deep component catalogue for the beam (to determine locations to search), and so the per-beam sourcefinding is activated when transient imaging is turned on.

• This results in a tar.gz file containing the Vaster outputs, that can be copied elsewhere for immediate use (a more complete archiving scheme is under development).

This is all done separately for each beam, in a specific transientImaging subdirectory.

The imaging is much simpler than the other continuum imaging. Since the dataset has already had the bulk of the continuum emission removed, only a very simple, shallow clean is done. Some parameters are provided to alter the preconditioning or deconvolution (see table below), although it is anticipated the defaults should suffice. The image can be made a different size/shape to the main continuum images, and no MFS imaging is done by default.

Variable	Default	Parset equivalent	Description
DO_TRANSIENT_IMAGING	false	none	Whether to run the transient imaging & detection
TRANSIENT_INTERVAL	900	none	Length of time in seconds for a single interval to be imaged.
Imaging parameters
NUM_PIXELS_TRANSIENT	3584	Images.shape (imager)	Number of pixels on the spatial dimension for the transient images
CELLSIZE_TRANSIENT	""	Images.cellsize(imager)	Angular size of spatial pixels for the transient images. If not provided, it defaults to the value of CELLSIZE_CONT
CLEAN_TRANSIENT_NUM_MAJORCYCLES	1	ncycles (imager)	Number of major cycles
CLEAN_TRANSIENT_ALGORITHM	BasisfunctionMFS	Clean.algorithm (Solvers)	The name of the clean algorithm to use.
CLEAN_TRANSIENT_MINORCYCLE_NITER	200	Clean.niter (Solvers)	The number of iterations for the minor cycle clean.
CLEAN_TRANSIENT_THRESHOLD_MINORCYCLE	“[30%, 5sigma, 0.5sigma]”	threshold.minorcycle (Solvers)	Thresholds for the minor cycle loop
CLEAN_TRANSIENT_GAIN	0.2	Clean.gain (Solvers)	The loop gain (fraction of peak subtracted per minor cycle).
CLEAN_TRANSIENT_PSFWIDTH	256	Clean.psfwidth (Solvers)	The width of the psf patch used in the minor cycle
CLEAN_TRANSIENT_SCALES	“[0]”	Clean.scales (Solvers)	Set of scales (in pixels) to use with the multi-scale clean.
CLEAN_TRANSIENT_POSITIVITY	"[false]"	Clean.positivity (Solvers)	Whether each scale used should be constrained to be positive only.
CLEAN_TRANSIENT_NOISEBOXSIZE	0	Clean.noiseboxsize(Solvers)	Size of the box used to determine the local noise value for setting thresholds (when a “sigma” threshold is given). A value of 0 means the entire image is used.
CLEAN_TRANSIENT_MASK	false	Clean.usemask (Solvers)	Set to true if we are using a clean mask image - consult Solvers for details on image name and content.
PRECONDITIONER_TRANSIENT_LIST	“[Wiener]”	preconditioner.Names (Solvers)	List of preconditioners to apply.
PRECONDITIONER_TRANSIENT_WIENER_ROBUSTNESS	-0.5	preconditioner.Wiener.robustness (Solvers)	Robustness value for the Wiener filter.
PRECONDITIONER_TRANSIENT_WIENER_TAPER	""	preconditioner.Wiener.taper (Solvers)	Size of gaussian taper applied in image domain to Wiener filter. Ignored if blank (ie. "").
PRECONDITIONER_TRANSIENT_GAUSS_TAPER	“[10arcsec, 10arcsec, 0deg]”	preconditioner.GaussianTaper (Solvers)	Size of the Gaussian taper (if provided in the preconditioner list) - either single value (for circular taper) or 3 values giving an elliptical size.
PRECONDITIONER_TRANSIENT_GAUSS_TAPER_TOL	0.005	preconditioner.GaussianTaper.tolerance (Solvers)	Fractional tolerance for the fitted beam size when PRECONDITIONER_CONTCUBE_GAUSS_TAPER_IS_PSF = true. The default is set to 0.5%
PRECONDITIONER_TRANSIENT_GAUSS_TAPER_IS_PSF	false	preconditioner.GaussianTaper.isPsfSize (Solvers)	Decide if rather than applying the specified taper, the taper should be adjusted to ensure that the output image planes have the specified resolution.
TRADITIONAL_WEIGHT_PARAM_TRANSIENT_LIST	""	uvweight (imager)	List of parameters for application of traditional weights.
TRADITIONAL_WEIGHT_TRANSIENT_ROBUSTNESS	-0.5	uvweight.robustness (imager)	The value of robustness. Only used if there is Robust among the list of parameters given by TRADITIONAL_WEIGHT_PARAM_TRANSIENT_LIST.
Transient Detection
TRANSIENT_DETECTION_KTYPELIST	“chisquare, peak, std”	none	Input parameters for Vaster
TRANSIENT_DETECTION_G_WIDTH	4	none	Input parameter for Vaster
TRANSIENT_DETECTION_CHUNK_0	100	none	Input parameter for Vaster
TRANSIENT_DETECTION_CHUNK_1	100	none	Input parameter for Vaster
Data handling
TRANSIENT_OUTPUT_DESTINATION	“”	none	Location to copy the output tar.gz files to - should be a directory. Leaving blank will keep the output files in the transientImaging directory.