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2_How to
SimonaRighini edited this page Apr 4, 2018
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Open a terminal and launch IDL:
$ IDL
Inside IDL, procedures are compiled as:
IDL> .r procname
And then launched as:
IDL> procname [, key=value, key2=’stringvalue’, /option]
Inside the command line, the various arguments must be comma—separated. If the procedure accepts input values, they are structured as key-value pairs. When the value to be passed is a string, it must be enclosed in ‘ ’. If options are available for a given procedure, they are enabled by using /
separate: | Used to reorganize the dataset in band-separated folders and, inside them, according to the nature of the source (flux calibrator, target source, skydip) |
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opacity: | (Optional) Used when needing to estimate the tau0 values, which are employed to compensate the subsequent calibrators/targets measurements inside the pipeline |
dataflagging: | (Optional) Used to visually inspect and flag each single subscan in the dataset. It exploits an interactive GUI |
runcalib: | Used in order to analyze the cross-scans acquired on flux density calibrators and to extract the counts-to-Jy factors to be subsequently employed in the target data calibration |
c2jtimeline: | Used in order to reconstruct a timeline (averaged values or linear interpolations) of the counts-to-Jy conversion factors. Notice: this procedure still needs refinements, yet it is compulsory to use it, as the target data calibration requires the counts-to-Jy values formatted as only c2jtimeline does. If you want to provide your own counts-to-Jy values, study such output format and filenames, and employ them to generate your custom list |
runtarget: | Used in order to reduce and calibrate the cross-scans acquired on target sources |
srcaver: | (Optional) Used in order to reprocess runtarget’s output and average the different measurements on a target basis |