There are two current options for getting reduced data at night on KCWI. You can grab the results of the automatic python pipeline, or you can set up the IDL pipeline for the observers to run themselves on new frames.
Open 3 local terminals and type the following two commands into each:
su kcwieng
ssh -X kcwidr@vm-sdr1
Use the first terminal to open the observers preferred cube display program. Our options include QFitsView, DS9, and atv within IDL.
Use the second terminal to copy the data over. There are two different scripts to do this based on if you want automatic Python pipeline results or do-it-yourself IDL results. Either way, this terminal is now occupied with rsyncing data over.
Python:
Using the automatic nighttime Python reduction, the data is already reduced. Copy the cubes over using:
~/rsync/getdata_py.sh YYYYMMDD YYYYmmmDD
For example,
~/rsync/getdata_py.sh 20220106 2022jan06
The script will check if the right YYYYmmmDD directory exists in /sdr1data/kcwidata, and make the directory if it doesn't exist. Then it will copy over the reduced KOA files with names starting with KB followed by the decimal UT date into the redux folder, and make links with the original KCWI frame numbers in the base directory. The frames will have suffixes indicating the type of cube copied over: _icube (original cube), _icubew (wavelength corrected cube), _icubed (wavelength and Differential Atmospheric Refraction corrected), and sometimes _icubes (all of the above plus standard-calibrated).
IDL:
Using the KCWI IDL pipeline, we copy over the raw data and the observer reduces it themselves. Copy the raw data over using:
~/rsync/getdata.sh kcwi# YYYYmmmDD YYYYmmmDD
For example,
~/rsync/getdata.sh kcwi8 2022jan06 2022jan06
The script will check if the right YYYYmmmDD directory exists in /sdr1data/kcwidata, and make the directory if it doesn't exist. Then it will copy over the raw data into the data directory.
Use the third terminal to cd to the data directory, /sdr1data/kcwidata/YYYYmmmDD, maneuver files as needed, and to run the IDL pipeline if you picked that option. You will need to source .cshrc to successfully start IDL using the idl command. After that, use the following commands to run the IDL pipeline, and repeat the commands as new data comes in.