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Robert Schulz edited this page Mar 25, 2019 · 32 revisions

Welcome to the dataqa wiki!

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)
  2. Run crosscal qa

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

  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

    1. Run mosaic

      • python make_mosaic_image.py <obs_id>
      • This script will create a directory: /data/apertif/<obs_id>/mosaic/ and place the mosaic image there (miriad image + fits image).
      • Good to know:
      • If not all of the beams have a continuum image there will be an error message, but the script will still run and create a mosaic from the beams that have a continuum image (fits file).
      • The script breaks if there are no beams at all to mosaic.
      • Other issues could be if the obs_id is too long. eg. more then 15 characters (regular obs_ids are 9). In this case miriad protests and the script breaks.
    2. Run validation

      • Example: `python run_continuum_validation.py <obs_id> --for_mosaic
  7. Put relevant information into Google-Doc

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