pipeline.hifv.cli.gotasks.hifv_checkflag

pipeline.hifv.cli.gotasks.hifv_checkflag = <pipeline.hifv.cli.gotasks.hifv_checkflag._hifv_checkflag object>

hifv_checkflag —- Run flagdata in rflag mode

——— parameter descriptions ———————————————

vis List of visibility data files. These may be ASDMs, tar files of ASDMs,

MSes, or tar files of MSes, If ASDM files are specified, they will be converted to MS format. example: vis=[‘X227.ms’, ‘asdms.tar.gz’]

checkflagmode – blank string default use of rflag on bandpass and delay calibrators

– use string ‘semi’ after hifv_semiFinalBPdcals() for executing rflag on calibrators – use string ‘bpd’, for the bandpass and delay calibrators:

execute rflag on all calibrated cross-hand corrected data; extend flags to all correlations execute rflag on all calibrated parallel-hand residual data; extend flags to all correlations execute tfcrop on all calibrated cross-hand corrected data,

per visibility; extend flags to all correlations

execute tfcrop on all calibrated parallel-hand corrected data,

per visibility; extend flags to all correlations

– use string ‘allcals’, for all the other calibrators, with delays and BPcal applied:

similar procedure as ‘bpd’ mode, but uses corrected data throughout

– use string ‘target’, for the target data:

similar procedure as ‘allcals’ mode, but with a higher SNR cutoff for rflag to avoid flagging data due to source structure, and with an additional series of tfcrop executions to make up for the higher SNR cutoff in rflag

– VLASS specific modes include ‘bpd-vlass’, ‘allcals-vlass’, and ‘target-vlass’

which calculate thresholds to use per spw/field/scan (action=’calculate’, then, per baseband/field/scan, replace all spw thresholds above the median with the median, before re-running rflag with the new thresholds. This has the effect of lowering the thresholds for spws with RFI to be closer to the RFI-free thresholds, and catches more of the RFI.

– Mode ‘vlass-imaging’ is similar to ‘target-vlass’, except that it executes on the split off target

data, intent=’*TARGET’, datacolumn=’data’ and uses a timedevscale of 4.0.

pipelinemode The pipeline operating mode. In ‘automatic’ mode the pipeline

determines the values of all context defined pipeline inputs automatically. In ‘interactive’ mode the user can set the pipeline context defined parameters manually. In ‘getinputs’ mode the user can check the settings of all pipeline parameters without running the task.

overwrite_modelcol Always write the model column, even if it already exists dryrun Run the commands (True) or generate the commands to be run but

do not execute (False). This is a pipeline task execution mode.

acceptresults Add the results of the task to the pipeline context (True) or

reject them (False). This is a pipeline task execution mode.

——— examples ———————————————————–

Output:

results – If pipeline mode is ‘getinputs’ then None is returned. Otherwise the results object for the pipeline task is returned.

Examples

1. Run RFLAG with associated heuristics in the VLA CASA pipeline.

hifv_checkflag()