Version 1.1 (2023/07/27)

This minor release includes the following improvements:

  • Speed up in imaging for data fractions < 1, by first concatenating in time the multiple MS files. This avoids the large penalty incurred when each measurement set is gridded individually by WSClean.

  • SageCal can be used for speeding up the DP3 predict step in the calibration workflow. Note that the use of SageCal prediction is still considered experimental!

  • Improvements in the determination of facet regions for large images.

  • Several improvements in the documentation.

  • Several bug fixes.

Version 1.0 (2023/06/08)

This release provides the following functionality:

  • Automated self calibration of HBA observations of “average” fields (i.e., those without very bright or extended sources).

  • Parallelization over multiple nodes of compute clusters (using Slurm).

  • Containerization via Docker or Singularity.

Know limitations, to be addressed in future releases, include the following:

  • Automated self calibration of low declination fields does not yet work well.

  • The use of screens should be considered experimental.

  • The use of GPUs is not yet supported except in imaging when using screens. Work is ongoing to add support for GPUs for prediction.

  • Processing times can be very long for large datasets. Considerable effort is being devoted to speeding up the slowest parts of calibration and imaging.

  • Only Stokes I imaging is currently done.