Subtract :: (Visibilties, SourceModel, GainModel) -> Visibilties

[Joshuaalbert]

We subtract the model visibilities for the bright sources from the data given the calibration solutions. This happens on a resolution different from cadenced calibration.

How:

• Cadenced calibration will produce solutions every validity_interval.
• DFTPredict is used to predict the bright sources for each baseline on the maximal time and frequency resolution.
• Sharding still happens by freq,time, therefore the calibration gains are broadcast to all every validity interval.
• These are stored until they are replaced. This implies a kernel of solve -> apply solutions for a period.

def single_validity_interval_loop():
  data = accumulate(solution_interval)
  solutions = calibrate(data)
  for i in validity_interval:
    data = accumulate(solution_interval)
    data = subtract(solutions, data)
    store_data(data)
    move_forward()