CASA EVLA Example Scripts: Difference between revisions
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If you would like to contribute an example script, and do not have access to the CASA Guides WIKI, you may email Miriam Krauss (mkrauss at nrao.edu). | If you would like to contribute an example script, and do not have access to the CASA Guides WIKI, you may email Miriam Krauss (mkrauss at nrao.edu). | ||
== | == Importing and calibrating data == | ||
The file [[File:Wideband_proc_dist.py]] contains three separate scripts to import, calibrate, and apply calibration to EVLA data. At each step, plots are created to help the observer evaluate the data quality and make necessary modifications to the data flags. It will send a notification email after completion of each step. | The file [[File:Wideband_proc_dist.py]] contains three separate scripts to import, calibrate, and apply calibration to EVLA data. At each step, plots are created to help the observer evaluate the data quality and make necessary modifications to the data flags. It will send a notification email after completion of each step. | ||
A simple reduction pipeline is described [[Transient reduction pipeline | here]], and provides a good guide for writing a script that can provide end-to-end processing. | |||
== Data visualization == | |||
Latest revision as of 23:11, 24 January 2011
Edit this file to contribute or update
Overview
Posted here are Python/CASA scripts which have been written to process EVLA data. These are provided as helpful examples on which to build customized scripts.
If you would like to contribute an example script, and do not have access to the CASA Guides WIKI, you may email Miriam Krauss (mkrauss at nrao.edu).
Importing and calibrating data
The file File:Wideband proc dist.py contains three separate scripts to import, calibrate, and apply calibration to EVLA data. At each step, plots are created to help the observer evaluate the data quality and make necessary modifications to the data flags. It will send a notification email after completion of each step.
A simple reduction pipeline is described here, and provides a good guide for writing a script that can provide end-to-end processing.
