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Scripts for data QA

Wrapper scripts for specific data QA should live at the top level. There are separate directories for scripts/code related to each type of data QA. E.g.

run_crosscalQA.py
crosscal
->ccal_plots.py

Procedure

At any time during the process you can run create_report.py <obs_id> to create the QA overview

1. Initial setup

   1. Log-in to Happili-01
   2. Open a screen session (optional, but recommended)
      • Example: screen -S dataqa
   3. Set environment for apercal (if not already done)
      • See https://github.com/apertif/apercal/wiki/Running-apercal-on-happili

2. Run crosscal qa

   • Example: python run_ccal_plots.py <scannumber> <fluxcal> [-p --/path/to/write/images/too]

3. Run selfcal qa

   • Example: python run_scal_plots.py <obs_id> <target>

4. Run continuum qa

   • Example: python run_continuum_validation.py <obs_id>
   • The script creates a directory for each beam in /data/apertif/<TASKID>/qa/continuum/<beam>/. Otherwise, there would be too many files in a single directory.

5. Run line qa

   • Example: python run_cube_stats.py <obs_id>

6. Run mosaic qa

   • Run validation
     • Example: `python run_continuum_validation.py <obs_id> --for_mosaic

7. Put relevant information into Google-Doc

Procedure to run QA for Apercal is described in the Google Doc