SKA SDP Pointing Offset Calibration Pipeline

This is a repository for the SDP pointing offset calibration pipeline. This repository reads Measurement Sets, optionally applies a static RFI mask (pulled from ska-telmodel-data in real time) and/or select some frequency range of interest, and then fits the 2-D Gaussian primary beams to the visibility or gain amplitudes.

The fitted parameters are the Gaussian centre (which provides the Cross-elevation and Elevation offsets), width (the fitted beamwidth), and height (in arbitrary units) and their uncertainties. These fitted parameters are then written to an HDF5 file created from a PointingTable and a text file generated by export_pointing_offset_data() for further analysis (see Data products of the pointing pipeline).

The pipeline reads Measurement Sets using the Visibility class from ska-sdp-datamodels. When an RFI mask is applied and/or some frequency range is selected, the modified visibility is created with the Visibility class for gain calibration (un-normalised G terms) or provides easy access to the visibilities and their associated parameters when fitting to them. These gains of each dish are solved for using the gain solver in the ska-sdp-func-python library. The primary beam modelling and fitting is performed with scikits.fitting following the procedure used by the SARAO team for computing the pointing offsets for the MeerKAT array.

The implementation of the pointing offset calibration pipeline is described in detail in the Observing Modes section.

The current pipeline can be executed as a CLI-based command line app (see Pointing Offset CLI Module), or deployed in SDP using the Pointing Offset Script.

Installation

Releases