This release adds preliminary support for Baseline Dependent Averaging (BDA), support for multiple prediction sources in DDECal, and support for a-terms when using IDG predictions. IDG prediction makes it computationally feasible to predict large source models.
Changes since v4.2:
- Add MSBDAReader, BDAAverager and MSBDAWriter steps that support BDA data.
- Support BDA data in the ScaleData step.
- DP3 now uses EveryBeam instead of LOFARBeam. This dependency is now required.
- DP3 now includes aocommon as an external git submodule.
- All code is now formatted using clang-format according to the Google C++ Style.
- CI improvements: Enforce code formatting, use SKA-compatible pipeline, add build without IDG, report test coverage.
- Enable various integration tests that were disabled.
- Convert FacetPredict into the IDGPredict step.
- Use new IDG bulk degridder in the IDGPredict step.
- Support a-terms in the IDGPredict step.
- Add ColumnReader step, for reading a specific column from a Measurement Set.
- Support multiple different prediction sources in DDECal.