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v1.15.3

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@Jammy2211 Jammy2211 released this 28 May 13:41
1.15.3
37eea7b

This release brings in a number of features for improved model-fitting, all of which come from an updated to PyAutoFit:

  • First class support for parallel Dynesty and Emcee model-fits. Previously, parallel fits were slow due to communication overheads, which are now handled correctly with PyAutoFit. One can expect a speed up close to the number of CPUs, for example a fit on 4 CPUs should take ~x4 less time to run. The API to perform a parallel fit is as follows:
search = af.DynestyStatic(
    path_prefix=path.join("imaging", "modeling"),
    name="mass[sie]_source[bulge]",
    unique_tag=dataset_name,
    nlive=50,
    number_of_cores=1, # Number of cores controls parallelization
)
  • In-built visualization tools for a non-linear search, using each non-linear search's inbuilt visualization libraries. Examples of each visualization are provided at the following link:

https://github.com/Jammy2211/autolens_workspace/tree/release/scripts/plot/search

  • Updated to the unique tag generation, which control the output model folder based on the model, search and name of the dataset.

  • Improved database tools for querying, including queries based on the name of the specific fit of the non-linear search and the dataset name unique tag.

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