Changelog¶
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.