This release corresponds to the Journal of Open Source Software (JOSS) publication of PyAutoCTI.
PyAutoFit:
Nautilusnow outputs results on the fly: PyAutoLabs/PyAutoFit#961- Output latent samples of a model-fit, which are parameters derived from a model which may be marginalized over:
PR: PyAutoLabs/PyAutoFit#994
Example: https://github.com/Jammy2211/autofit_workspace/blob/release/notebooks/cookbooks/analysis.ipynb
model.infofile displays complex models in a more concise and readable way: PyAutoLabs/PyAutoFit#1012- All samples with a weight below an input value are now removed from
samples.csvto save hard disk space: PyAutoLabs/PyAutoFit#979 - Documentation describing autofit scientific workflow: PyAutoLabs/PyAutoFit#1011
- Refactor visualization into stand alone module: PyAutoLabs/PyAutoFit#995
- Refactor how results are returned after a search: PyAutoLabs/PyAutoFit#989
- Improved parallelism logging: PyAutoLabs/PyAutoFit#1009
- Likelihood consistency check now performed internally: PyAutoLabs/PyAutoFit#987
- Generation of initial search samples is now performed in parallel: PyAutoLabs/PyAutoFit#997
- No longer store
search_internalon hard-disk. simplifying source code internals: PyAutoLabs/PyAutoFit#938 - Multiple small bug fixes and improvements to interface.