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 either the simager task (the default), or the new imager, creating a set of spectral cubes. The new imager provides the ability to image in the barycentric reference frame, and allows (for efficiency purposes) the option of writing out multiple sub-cubes (each having a subset of the full range of channels).

A final task can perform image-based continuum subtraction. There are two choices for this step, made via the SPECTRAL_IMSUB_SCRIPT parameter. The first uses the robust_contsub.py script in the ACES directory to fit and subtract a low-order polynomial to each spectrum in the cube separately. The second uses the contsub_im.py script which uses a Savitzky-Golay filter to find and remove the spectral baseline, again in each spectrum of the cube separately. These tasks are intended as demonstrations of this capability - there will be an ASKAPsoft equivalent to this in a future release. The task assumes that the requested python script is in $ACES/tools - if it is not found, the task will not run.

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.

A note on the imagers and the output formats. The default approach is to use simager to produce the spectral-line cubes. The new imager application imager (imager (under test)) can be used by setting DO_ALT_IMAGER_SPECTRAL to true.

The default output format is CASA images, although FITS files can be written directly by setting IMAGETYPE_SPECTRAL to fits (rather than casa). This will only work with the new imager, as simager does not yet have this functionality. This mode is still in development, so may not be completely reliable. The recommended method for getting images into FITS format is still to use the DO_CONVERT_TO_FITS flag, which makes use of the FITS conversion application. A single FITS file can be produced by setting ALT_IMAGER_SINGLE_FILE=true.

Variable Default Parset equivalent Description
DO_SPECTRAL_IMAGING false none Whether to do the spectral-line imaging
JOB_TIME_SPECTRAL_IMAGE JOB_TIME_DEFAULT (12:00:00) none Time request for imaging the spectral-line data
IMAGETYPE_SPECTRAL casa imagetype (imager (under test)) Image format to use - can be either ‘casa’ or ‘fits’, although ‘fits’ can only be given in conjunction with DO_ALT_IMAGER_SPECTRAL=true.
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.
JOB_TIME_SPECTRAL_SPLIT JOB_TIME_DEFAULT (12:00:00) none Time request for splitting out a subset of the spectral data
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 10 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. Although the simager will only process single channels, the default is made larger than 1 (the default for mssplit) so that the mssplit job completes in a reasonable length of time.
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 imaging).
JOB_TIME_SPECTRAL_APPLYCAL JOB_TIME_DEFAULT (12:00:00) none Time request for applying the gains calibration to the spectral data
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.
JOB_TIME_SPECTRAL_CONTSUB JOB_TIME_DEFAULT (12:00:00) none Time request for subtracting the continuum from the spectral data
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 10uJy 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.
Basic variables for imaging      
NUM_CPUS_SPECIMG_SCI 200 none The total number of cores 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 cores per node to use (max 20).
IMAGE_BASE_SPECTRAL i.SB%s.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. The %s wildcard will be resolved into the scheduling block ID.
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 1536 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 4 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_SNAPSHOT_LONGTRACK true snapshotimaging.longtrack (Gridders) The longtrack parameter controlling how the best-fit W plane is determined when using snapshots.
GRIDDER_SPECTRAL_SNAPSHOT_CLIPPING 0 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_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 5000 Clean.niter (Solvers) The number of iterations for the minor cycle clean.
CLEAN_SPECTRAL_GAIN 0.1 Clean.gain (Solvers) The loop gain (fraction of peak subtracted per minor cycle).
CLEAN_SPECTRAL_PSFWIDTH 512 Clean.psfwidth (Solvers) The width of the psf patch used in the 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 “[50%, 30mJy]” threshold.minorcycle (Solvers) Threshold for the minor cycle loop.
CLEAN_SPECTRAL_THRESHOLD_MAJORCYCLE 20mJy 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 5 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]” preconditioner.Names (Solvers) List of preconditioners to apply.
PRECONDITIONER_SPECTRAL_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_SPECTRAL_WIENER_ROBUSTNESS
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. “”).
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 “[30arcsec, 30arcsec, 0deg]”).
RESTORING_BEAM_CUTOFF_SPECTRAL 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.
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’
New imager parameters      
DO_ALT_IMAGER_SPECTRAL “” none If true, the spectral-line imaging is done by imager (imager (under test)). If false, it is done by simager (simager). When true, the following parameters are used. If left blank (the default), the value is given by the overall parameter DO_ALT_IMAGER (see User Parameters - Pipeline & job control).
NCHAN_PER_CORE_SL 54 nchanpercore (imager (under test)) The number of channels each core will process.
USE_TMPFS false usetmpfs (imager (under test)) Whether to store the visibilities in shared memory. This will give a performance boost at the expense of memory usage. Better used for processing continuum data.
TMPFS /dev/shm tmpfs (imager (under test)) Location of the shared memory.
NUM_SPECTRAL_WRITERS 1 nwriters (imager (under test)) The number of writers used by imager. Unless ALT_IMAGER_SINGLE_FILE=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.
ALT_IMAGER_SINGLE_FILE false singleoutputfile (imager (under test)) Whether to write a single cube, even with multiple writers (ie. NUM_SPECTRAL_WRITERS>1). Only works when IMAGETYPE_SPECTRAL=fits
DO_BARY true barycentre (imager (under test)) Whether to write the spectral cubes in the Barycentric reference frame.
Image-based continuum subtraction      
DO_SPECTRAL_IMSUB false none Whether to run an image-based continuum-subtraction task on the spectral cube after creation.
JOB_TIME_SPECTRAL_IMCONTSUB JOB_TIME_DEFAULT (12:00:00) none Time request for image-based continuum subtraction
SPECTRAL_IMSUB_SCRIPT “robust_contsub.py” none The name of the script from the ACES repository to use for image-based continuum subtraction. The only two accepted values are “robust_contsub.py” and “contsub_im.py”. Anything else reverts to the default.
SPECTRAL_IMSUB_VERBOSE true none Whether to use verbose output in the logging for the image-based continuum subtraction.
SPECTRAL_IMSUB_THRESHOLD 2.0 none (‘threshold’ parameter in robust_contsub.py) Threshold [sigma] to mask outliers prior to fitting the continuum baseline in the “robust_contsub.py” version of the image-based continuum-subtraction.
SPECTRAL_IMSUB_FIT_ORDER 2 none (‘fit_order’ parameter in robust_contsub.py) Order of the polynomial to fit to the continuum baseline in the “robust_contsub.py” version of the image-based continuum subtraction.
SPECTRAL_IMSUB_CHAN_SAMPLING 1 none (‘n_every’ parameter in robust_contsub.py) If set to n, we use only every nth channel in the polynomial fit (1 uses every channel). Only for “robust_contsub.py”
SPECTRAL_IMSUB_LOG_SAMPLING 1 none (‘log_every’ parameter in robust_contsub.py) How frequently the log messages from “robust_contsub.py” should be written (1 means every channel).
SPECTRAL_IMSUB_SG_FILTERWIDTH 200 none (‘filterwidth’ parameter in contsub_im.py) The half-width of the Savitzky-Golay filter for baseline smoothing in the “contsub_im.py” script.
SPECTRAL_IMSUB_SG_BINWIDTH 4 none (‘binwidth’ parameter in contsub_im.py) The bin width used for binning the spectrum before continuum subtraction (“contsub_im.py” only).

Previous topic

User Parameters - Continuum imaging

Next topic

User Parameters - Mosaicking

This Page