User Parameters - Preparation of the Science field data¶
These parameters govern the pre-processing needed for the science field, to split by beam, apply the bandpass (although none of the parameters listed here relate to that), flag, and average to continuum resolution.
The splitting is done by beam, and optionally by particular scans and/or fields (where the latter are selected on the basis of the FIELD NAME in the MS).
As noted in User Parameters - Data Location & Beam Selection, when an observation was taken in one-field-per-beam mode, and no selection on scans or channels is done, and there is only a single beam in the MS, then the beam MSs are copied instead of using mssplit. This will run much faster.
Once copied or split, a number of pre-imaging tasks are run. The
default behaviour is to run these in a single slurm job, but this can
be separated into a job per task by setting
SINGLE_JOB_PREIMAGING=false. Using a single job will work better
in a large slurm queue.
The raw measurement set is first calibrated with the bandpass calibration table derived previously (see User Parameters - Bandpass Calibration). Once calibrated, the dataset will be flagged to remove interference.
As is the case for the bandpass calibrator dataset, the MS is flagged in two passes. First, a combination of selection rules (allowing flagging of channels, time ranges, antennas & baselines, and autocorrelations) and (optionally) a simple flat amplitude threshold are applied. Then a sequence of Stokes-V flagging and dynamic flagging of amplitudes is done, optionally integrating over or across individual spectra. Each of these steps is selectable via input parameters.
The DO_PREFLAG_SCIENCE parameter allows user to flag science data
based on already available information from processing of the bandpass
data. This is used to flag really bad antennas using robust outlier
detection methods, along with channels that exceed a given n-sigma
threshold in the residuals from the smooth fit to the bandpass
solutions (thereby allowing RFI-affected channels in the bandpass data
to be flagged and not contaminate the science data).
The USER_DEFINED_FLAGS parameter further allows users to specify rule-based
flagging directives using an ascii FLAG_DIRECTIVE_FILE that the pipeline can
interpret and use for flagging the specified data. The directive file can have
as many rows as the number of rules necessary.
Each row will be used to generate a new rule.
All rules for the same beam will be used in a single Cflag parset for that beam
The first column must be used to specify the beam and the subsequent part of a row specifies elements corresponding to that beam that one wants flagged. Currently supported rules for flagging include:
Antenna/Baseline pairs
SPW
TimeRange
UVRange
Example syntax for a directive:
BEAM-NN -a AntNum -s spw:channelRange -t timeRange -u uvRange
The pipeline allows option to additionally flag all continuum and spectral line visibilities for channels with flagging percentages above a specified threshold. This is useful in mitigating adverse effects on imaging spectral channels with unusually high flagging percentages.
The formats for each of these selections (Antenna, SPW, TimeRange, etc.) must be compatible with Cflag. For details on how to specify these, see: http://www.aoc.nrao.edu/~sbhatnag/misc/msselection/msselection.html
Again, there is an option to use the
AOFlagger tool (written by Andre Offringa) to do the flagging. This
can be turned on by FLAG_WITH_AOFLAGGER, or
FLAG_SCIENCE_WITH_AOFLAGGER & FLAG_SCIENCE_AV_WITH_AOFLAGGER
(to just do it for the full-spectral-resolution or averaged science
data respectively). You can provide a strategy file via
AOFLAGGER_STRATEGY or AOFLAGGER_STRATEGY_SCIENCE &
AOFLAGGER_STRATEGY_SCIENCE_AV, with access to some of the
aoflagger parameters provided - see the table below. These strategy
files need to be created prior to running the pipeline.
The dataset used for continuum imaging is created by averaging the frequency channels. The default amount of averaging is determined from the scheduling block parset parameters:
common.cp.ingest_mode=avg– no averaging needed (data taken in continuum mode)
common.cp.ingest_mode=full– data taken in spectral mode. Then:
common.target.src%d.corrmode=standard- 54 channelselse, common.target.src%d.corrmode will be something like zoom32x, so we use 32x54=1728 channels.
The aim here is to get a 1MHz-resolution MS that can be imaged to
produce the continuum image and run the self-calibration. The parset
settings can be overridden by the use of NUM_CHAN_TO_AVERAGE. If
the first option is encountered (common.cp.ingest_mode=avg), the
jobs to do the averaging (and flagging of the averaged data) are
skipped, and we make a symbolic link to the original MS to represent
the averaged version.
It is possible to combine the channels using a median rather than an
average - this will increase the noise level, but can be superior in
rejecting very bright signal (e.g. narrow band signal affecting a
small number of channels). This can be turned on by setting
AVERAGING_USES_MEDIAN=true.
Once the averaged dataset has been created, a second round of flagging can be done on it, to flag any additional features that the averaging process may have enhanced.
The default behaviour is to process all fields within the science MS
(interleaving, for instance, makes use of multiple fields), with each
field being processed in its own sub-directory. The field selection is
done in the splitting task, at the same time as the beam selection. It
is possible, however, to select a single field to process via the
FIELD_SELECTION_SCIENCE parameter (by giving the field name).
The pipeline has two options to speed up processing - either by
splitting the msdata in time or by using parallel write access to the
MS. If chosen, the timewise splitting of the measurement sets for each
beam are done upfront at the copy/split step. This allows parallel
execution of the non-imaging tasks (BandpassApplication, Flagging,
Averaging and ContinuumSubtraction) on the cluster, and helps attain a
massive reduction in processing times. The imaging is done per beam
using data in ALL the TimeWindows by combining the TimeWise split data
in an intermediate step. For details on making use of this feature,
see the section on Processing by splitting data in time in the
table below. The parallel write to the msdata can only be used if
askapsoft was built using a patched version of casacore. In that case
use USE_PARALLEL_WRITE_MS=true to enable this mode. This will
allow calibration application, Flagging and ContinuumSubtraction to
run in parallel, but without the need to split up (and merge) the
data. Combining the two speedup options is not recommended.
Variable |
Default |
Parset equivalent |
Description |
|---|---|---|---|
Job selection |
|||
|
true |
none |
Whether to split out the given beam from the science MS |
|
|
none |
Time request for splitting the science MS |
|
true |
none |
Whether to propagate flags from Bandpass data to the splitted science MS. Currently, only BAD antenna flags are propagated |
|
20 |
none |
The threshold, in multiples of ‘sigma’, that determines whether a given channel is flagged by the preflagger. |
|
true |
none |
If true, flag all visibilities for fine channels in science data that
has a flagged% > |
|
true |
none |
If true, flag all visibilities for coarse channels in science data
that has a flagged% > |
|
50.0 |
none |
Flagging Threshold (in %) used in the additional flagging of visibilities. |
|
false |
none |
Whether to propagate flag directives specified in an ASCII file:
|
|
|
none |
ASCII file with each row specifying a Beam number and flagging criteria for that beam. For example:
In general each directive should be specified in a single row as:
|
|
true |
none |
Whether to flag the (splitted) science MS |
|
|
none |
Time request for flagging the science MS |
|
true |
none |
Whether to apply the bandpass calibration to the science observation |
|
|
none |
Time request for applying the bandpass to the science data |
|
19 |
none |
Number of cores for the job to apply the bandpass to the science data. |
|
true |
none |
Whether to average the science MS to continuum resolution |
|
|
none |
Time request for averaging the channels of the science data |
Data selection |
|||
|
no default (see description) |
This allows selection of particular scans from the science observation. If not provided, no scan selection is done (all scans are included in the output MS). |
|
|
no default (see description) |
This allows selection of particular FIELD NAMEs from the science observation. If not provided, all fields are done. The value must be just the field name - not surrounded by square brackets (which is a possible format for mssplit.fields). This is because the value iwll be matched to field names from the measurement set. |
|
|
scienceData.%t.SB%s.%b.ms |
none |
Base name for the science observation measurement set after splitting. The wildcard %s will be replaced by the scheduling block ID, %t will be replaced by the “target” or scheduling block alias, and %b will be replaced by the string “FIELD.beamBB”, where FIELD represents the FIELD id, and BB the (zero-based) beam number (scienceData.LMC.SB1234.LMCA.beam00.ms etc). |
|
no default (see description) |
dataset (cimager) |
The name of the averaged measurement set that will be
imaged by the continuum imager. Provide this if you want
to skip the bandpass calibration and averaging steps
(perhaps you’ve already done them). The wildcard %b, if
present, will be replaced with “FIELD.beamBB”, as described above. If
not provided, the averaged MS name will be derived from
|
|
|
Range of channels in science observation (used in splitting and
averaging). This must (for now) be the same as
|
|
|
|
Number of channels to be averaged to create continuum measurement set. Value is determined by the scheduling block parset by default, but can be overridden by providing a value here. |
|
|
false |
usemedian (mssplit (Measurement Splitting/Averaging Utility)) |
If true, the channels are combined using a median rather than average. |
|
1 |
stman.tilenchan (mssplit (Measurement Splitting/Averaging Utility)) |
The number of channels in the tile size used for the averaged MS. |
Initial flagging |
|||
|
true |
none |
Whether to do the dynamic flagging, after the rule-based and simple flat-amplitude flagging is done |
|
4.0 |
amplitude_flagger.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging science field data [sigma] |
|
true |
amplitude_flagger.integrateSpectra (cflag / cflagger (Flagging Utility)) |
Whether to flag channels in the time-averaged spectra during the dynamic flagging task. |
|
4.0 |
amplitude_flagger.integrateSpectra.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging science field data in integrateSpectra mode [sigma] |
|
false |
amplitude_flagger.integrateTimes (cflag / cflagger (Flagging Utility)) |
Whether to flag time samples in the spectrally averaged time-series during the dynamic flagging task. |
|
4.0 |
amplitude_flagger.integrateTimes.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging science field data in integrateTimes mode [sigma] |
|
true |
none |
Whether to do the Stokes-V flagging on the science data, after the rule-based and simple flat-amplitude flagging is done |
|
true |
stokesv_flagger.useRobustStatistics (cflag / cflagger (Flagging Utility)) |
Whether to use robust statistics (median and inter-quartile range) in computing the Stokes-V statistics. |
|
4.0 |
stokesv_flagger.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the science field data [sigma] |
|
true |
stokesv_flagger.integrateSpectra (cflag / cflagger (Flagging Utility)) |
Whether to flag channels in the time-averaged spectra during the Stokes-V flagging task. |
|
4.0 |
stokesv_flagger.integrateSpectra.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the science field data in integrateSpectra mode [sigma] |
|
false |
stokesv_flagger.integrateTimes (cflag / cflagger (Flagging Utility)) |
Whether to flag time samples in the spectrally averaged time-series during the Stokes-V flagging task. |
|
4.0 |
stokesv_flagger.integrateTimes.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the science field data in integrateTimes mode [sigma] |
|
false |
none |
Whether to apply a flag amplitude flux threshold to the data. |
|
amplitude_flagger.high (cflag / cflagger (Flagging Utility)) |
Simple amplitude threshold applied when flagging science field data.
If set to blank ( |
|
|
|
amplitude_flagger.low (cflag / cflagger (Flagging Utility)) |
Lower threshold for the simple amplitude flagging. If set
to blank ( |
|
|
elevation_flagger.low (cflag / cflagger (Flagging Utility)) |
Visibilities below this elevation (degrees) will be flagged. If set
to blank ( |
|
|
elevation_flagger.high (cflag / cflagger (Flagging Utility)) |
Visibilities above this elevation (degrees) will be flagged. If set
to blank ( |
|
|
selection_flagger.<rule>.antenna (cflag / cflagger (Flagging Utility)) |
Allows flagging of antennas or baselines. For example, to
flag out the 1-3 baseline, set this to |
|
|
selection_flagger.<rule>.spw (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified range of channels. For example, to flag
out the first 100 channnels, use |
|
|
selection_flagger.<rule>.timerange (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified time range(s). The string given is
passed directly to the |
|
|
selection_flagger.<rule>.uvrange (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified UV range(s). The string given is
passed directly to the |
|
false |
selection_flagger.<rule>.autocorr |
If true, then autocorrelations will be flagged. |
Flagging of averaged data |
|||
|
true |
none |
Whether to do an additional step of flagging on the channel-averaged MS proior to imaging. |
|
true |
none |
Whether to do the dynamic flagging on the averaged science data, after the simple flat-amplitude flagging is done |
|
4.0 |
amplitude_flagger.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging the averaged science field data [sigma] |
|
true |
amplitude_flagger.integrateSpectra (cflag / cflagger (Flagging Utility)) |
Whether to flag channels in the time-averaged spectra during the dynamic flagging task. |
|
4.0 |
amplitude_flagger.integrateSpectra.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging the averaged science field data in integrateSpectra mode [sigma] |
|
false |
amplitude_flagger.integrateTimes (cflag / cflagger (Flagging Utility)) |
Whether to flag time samples in the spectrally averaged time-series during the dynamic flagging task. |
|
4.0 |
amplitude_flagger.integrateTimes.threshold (cflag / cflagger (Flagging Utility)) |
Dynamic threshold applied to amplitudes when flagging the averaged science field data in integrateTimes mode [sigma] |
|
true |
none |
Whether to do the Stokes-V flagging on the averaged science data, after the rule-based and simple flat-amplitude flagging is done |
|
true |
stokesv_flagger.useRobustStatistics (cflag / cflagger (Flagging Utility)) |
Whether to use robust statistics (median and inter-quartile range) in computing the Stokes-V statistics. |
|
4.0 |
stokesv_flagger.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the averaged science field data [sigma] |
|
true |
stokesv_flagger.integrateSpectra (cflag / cflagger (Flagging Utility)) |
Whether to flag channels in the time-averaged spectra during the Stokes-V flagging task. |
|
4.0 |
stokesv_flagger.integrateSpectra.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the averaged science field data in integrateSpectra mode [sigma] |
|
false |
stokesv_flagger.integrateTimes (cflag / cflagger (Flagging Utility)) |
Whether to flag time samples in the spectrally averaged time-series during the Stokes-V flagging task. |
|
4.0 |
stokesv_flagger.integrateTimes.threshold (cflag / cflagger (Flagging Utility)) |
Threshold applied to amplitudes when flagging the Stokes-V for the averaged science field data in integrateTimes mode [sigma] |
|
false |
none |
Whether to apply a flag amplitude flux threshold to the averaged science data. |
|
amplitude_flagger.high (cflag / cflagger (Flagging Utility)) |
Simple amplitude threshold applied when flagging the averaged science
field data. If set to blank
( |
|
|
|
amplitude_flagger.low (cflag / cflagger (Flagging Utility)) |
Lower threshold for the simple amplitude flagging on the averaged
data. If set to blank ( |
|
|
selection_flagger.<rule>.spw (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified range of channels. For example, to flag
out the first 100 channnels, use |
|
|
selection_flagger.<rule>.timerange (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified time range(s). The string given is
passed directly to the |
|
|
selection_flagger.<rule>.uvrange (cflag / cflagger (Flagging Utility)) |
Allows flagging of a specified UV range(s). The string given is
passed directly to the |
Using AOFlagger for flagging |
|||
|
false |
none |
Use AOFlagger for all flagging tasks in the pipeline. This overrides the individual task level switches. |
|
false |
none |
Use AOFlagger for the flagging of the full-spectral-resolution science dataset. This and the next parameter allows differentiation between the different flagging tasks in the pipeline. |
|
false |
none |
Use AOFlagger for the flagging of the averaged science dataset. |
|
|
none |
The strategy file to use for all AOFlagger tasks in the pipeline. Giving this a value will apply this one strategy file to all flagging jobs. The strategy file needs to be provided by the user. |
|
|
none |
The strategy file to be used for the full-spectral-resolution science
dataset. This will be overridden by |
|
|
none |
The strategy file to be used for the averaged science dataset. This
will be overridden by |
|
true |
none |
Verbose output for AOFlagger |
|
auto |
none |
Read mode for AOflagger. This can take the value of one of “auto”, “direct”, “indirect”, or “memory”. These trigger the following respective command-line options for AOflagger: “-auto-read-mode”, “-direct-read”, “-indirect-read”, “-memory-read”. |
|
false |
none |
When true, the command-line argument “-uvw” is added to the AOFlagger command. This reads uvw values (some exotic strategies require these). |
Processing by splitting data in time |
|||
|
true |
none |
By default, the non-imaging jobs – bandpass application, flagging, averaging, ccontsubtract – will be done in data that has been split into TimeWindows (see below for TimeWindow interval selection param). This will speed-up the processing, especially when the observation duration exceeds a few hours. |
|
60 |
none |
If |
Processing by parallel write to ms data |
|||
|
false |
none |
The non-imaging jobs – bandpass application, flagging, ccontsubtract – will be done using parallel writes to the ms data. This will speed-up the processing and reduce the number of separate jobs to run. It is faster than timewise splitting and generally should not be combined with that option. |