Baseline dependent averaging scripts

This is a set of python scripts for simulations of baseline dependent averaging using CASA, OSKAR, and WSClean.

Test simulations:

• Test simulation 1

Some benchmark results (work in progress) can be found here.

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Timings [1Feb2016]

Total run time of 839.5 s - simulation (104s) - corrupt (239s) - bda (80.7s) - ~20s*6 calibrations = 120s - imaging > 250s (using lots of combinations **)

** imaging costs will drop considerably if we don't image everything!

• Simulation1 (model): 50 times (20 over-sample) => 1000 time oskar time steps.
  • 104.3 s
• Simulation2 (model ref): 50 times (no sky)
  • 5.7 s
• Corrupt MS (corrupt + applycal):
  • copy ms: 4.9 s
  • create MODEL_DATA and CORRECTED_DATA columns: 45.1 s
  • copy DATA to MODEL_DATA: 2.4 s
  • Create calibration table for corruptions: 23.4 s
  • Fill calibration table: 14.9 s
  • Apply corruptions: 146.2 s
  • Update DATA column (copy CORRECTED_DATA to DATA?): 1.4 s
  • Total: 239.4 s
• Average (collapse over-sample)
  • ???
• Add noise
  • ???
• Average (BDA) (mstrasnform)
  • Model -> model_bda: 23.4s
  • Corrupted -> corrupted_bda: 28.6 s
  • Corrupted_noisy -> corrupted_noisy_bda: 28.7 s
• Expand BDA prior to calibration
  • ???
• Calibrate (gaincal + applycal)
  • corrupted: 13.5 s + 7.3 s
  • corrupted_bda: 12.6 s + 4.2 s
  • corrupted_bda_expanded: 11.4 s + 7.2 s
  • corrupted noisy: 11.3 s + 7.3 s
  • corrupted_noisy_bda: 9.2 s + 4.2 s
  • corrupted_noisy_bda_expanded: 11.7 s + 7.2 s
• BDA (the expanded data sets)
  • calibrated_bda_expanded: 28.3 s
  • calibrated_noisy_bda_expanded: 28.4 s
• Imaging (CASA imtool) (uniform, on target, off target, DATA, CORRECTED, MODEL):
  • calibrated: (3.7 + 7.3 + 3.5 + 7.2 + 3.6 + 7.3)
  • calibrated bda: (2.1 + 4.1 + 2.1 + 4.1 + 2.1 + 4.3)
  • calibrated bda expanded: (3.7 + 7.1 + 3.5 + 7.1 + 3.7 + 7.4)
  • calibrated bda expanded bda: (2.1 + 4.1 + 2.1 + 4.0 + 2.1 + 4.3)
  • calibrated noisy: 3.4 + 7.1 + 3.6 + 7.2 + 3.8 + 7.4
  • calibrated noisy bda: 2.1 + 4.1 + 2.0 + 4.0 + 2.1 + 4.2
  • calibrated noisy bda expanded: 3.6 + 7.3 + 3.7 + 7.2 + 3.7 + 7.4
  • calibrated noisy bda expanded bda: 2.0 + 4.1 + 2.0 + 4.1 + 2.1 + 4.3
  • corrupted: 3.6 + 7.2 (uniform DATA, on and off target)
  • corrupted_bda: 2.1 + 4.1 (uniform DATA, on and off target)
  • corrupted_bda_expanded: 3.6 + 7.2 (uniform DATA, on and off target)
  • corrupted_noisy: 3.6 + 7.2 (uniform DATA, on and off target)
  • corrupted_noisy_bda: 2.0 + 4.0 (uniform DATA, on and off target)
  • corrupted_noisy_bda_expanded: 3.6 + 7.3 (uniform DATA, on and off target)
  • model: 3.4 + 6.9 (uniform DATA, off + on target)
  • model_bda: 2.1 + 4.2 (uniform DATA, off + on target)
  • model_ref: 3.6 + 7.2 (uniform DATA, off + on target)
• Diffs
  • ??