Radio Astronomy Simulation, Calibration and Imaging Library
The Radio Astronomy Simulation, Calibration and Imaging Library expresses radio interferometry calibration and imaging algorithms in python and numpy. The interfaces all operate with familiar data structures such as image, visibility table, gain table, etc.
As of version 1.0.0, the library mostly contains high-level workflows and pipelines, while the data models and a large number of processing components (functions) have been migrated to ska-sdp-datamodels and ska-sdp-func-python, which are directly used within RASCIL.
To achieve sufficient performance we take a dual pronged approach - using threaded libraries for shared memory processing, and the Dask library for distributed processing.
The role of the RASCIL in SKA Science Data Processing (SDP)
RASCIL was developed in SDP under the name ARL (Algorithm Reference Library) with the emphasis of creating reference versions of standard algorithms. The ARL was therefore designed to present primarily imaging algorithms in a simple Python-based form so that the implemented functions could be seen and understood easily. This also fulfilled the requirement of providing a simple test version where algorithms could be tested and compared as necessary.
For an overview of the SDP see the SDP CDR documentation
More details can be found at: SKA1 SDP Algorithm Reference Library (ARL) Report
Subsequent to the conclusion of the SDP project, it became clear that ARL could play a larger role than being limited to a reference library. Hence, it was renamed to the Radio Astronomy Simulation, Calibration and Imaging Library (RASCIL) and is undergoing continued development. The Algorithm Reference Library (ARL) is now frozen. The background motivation and requirements of the ARL/RASCIL are detailed further in Background.
- RASCIL development