solve_gaintable

ska_sdp_func_python.calibration.solvers.solve_gaintable(vis: Visibility, modelvis: Visibility = None, gain_table=None, phase_only=True, niter=200, tol=1e-06, crosspol=False, normalise_gains='mean', jones_type='T', timeslice=None, refant=0) → GainTable[source]

Solve a gain table by fitting an observed visibility to a model visibility.

If modelvis is None, a point source model is assumed.

Parameters:

  • vis – Visibility containing the observed data_models

  • modelvis – Visibility containing the visibility predicted by a model

  • gain_table – Existing gaintable

  • phase_only – Solve only for the phases (default=True)

  • niter – Number of iterations (default 30)

  • tol – Iteration stops when the fractional change in the gain solution is below this tolerance

  • crosspol – Do solutions including cross polarisations i.e. XY, YX or RL, LR

  • normalise_gains – Normalises the gains (default=”mean”) options are None, “mean”, “median”. None means no normalization.

  • jones_type – Type of calibration matrix T or G or B

  • timeslice – Time interval between solutions (s)

  • refant – Reference antenna (default 0)

Returns:

GainTable containing solution