calibrate_chain
- ska_sdp_func_python.calibration.chain_calibration.calibrate_chain(vis, model_vis, gaintables=None, calibration_context='T', controls=None, iteration=0, tol=1e-06)[source]
Calibrate using algorithm specified by calibration_context.
The context string can denote a sequence of calibrations e.g. TGB. Currently, we do not support inputting different timescales.
- Parameters:
vis – Visibility containing the observed data_models
model_vis – Visibility containing the visibility predicted by a model
gaintables – Existing GainTables (GainTable, list or dict)
calibration_context – Calibration contexts in order of correction e.g. ‘TGB’
controls – Controls dictionary, modified as necessary
iteration – Iteration number to be compared to the ‘first_selfcal’ field.
tol – Iteration stops when the fractional change in the gain solution is below this tolerance
- Returns:
Calibrated data_models, dict(GainTables)