Self-Calibrating with Multiple Models

Both selfcal and gpscal can be given multiple input model images. The input models can be cubes for multi-channel data. These different models represent some different aspect of the data. For example, the data could contain multiple pointing centres from a mosaiced observation or multiple spectral lines. The self-calibration tasks assume that the gains are not dependent on these different aspects of the data (e.g. the gains are independent of frequency and pointing centre). All the information will be used in a simultaneous solution of the gains. The self-calibration tasks will generally determine the appropriate correspondence between data and model (e.g. it will associate the data from a particular pointing with a model with the same pointing). There are, however, some caveats described below.