Autofit

This update is mostly bug fixes and small improvements, with no major new functionality added.

What's Changed

* Feature/enviroment warning by Jammy2211 in https://github.com/rhayes777/PyAutoFit/pull/1077
* cache hdus to avoid object deletion causing files to be closed by rhayes777 in https://github.com/rhayes777/PyAutoFit/pull/1081
* feature/constant comparison by rhayes777 in https://github.com/rhayes777/PyAutoFit/pull/1080
* Remove database test path by Jammy2211 in https://github.com/rhayes777/PyAutoFit/pull/1083
* analysis_summed_latent by Jammy2211 in https://github.com/rhayes777/PyAutoFit/pull/1084
* monkey patch abstract_search.gc during testing to prevent expensive calls to gc.collect() by rhayes777 in https://github.com/rhayes777/PyAutoFit/pull/1088
* feature/aggregate summary by rhayes777 in https://github.com/rhayes777/PyAutoFit/pull/1089


**Full Changelog**: https://github.com/rhayes777/PyAutoFit/compare/2024.11.13.2...2025.1.18.7

Garbage collection and other things to improve memory use.

Minor release with stability updates and one main feature.

- Sensitivity Mapping improvements.

- Start point for MCMC.

This release updates all projects to support Python 3.12, with support tested for Python 3.9 - 3.12 and 3.11 regarded as most stable.

This includes many project dependency updates:

https://github.com/rhayes777/PyAutoFit/blob/main/requirements.txt
https://github.com/rhayes777/PyAutoFit/blob/main/optional_requirements.txt

**PyAutoFit:**

https://github.com/rhayes777/PyAutoFit/pulls?q=is%3Apr+is%3Aclosed

- Improvements to HowToFit lectures: https://github.com/rhayes777/PyAutoFit/pull/1022
- Support for NumPy arrays in model composition and prior creation, for example creating an `ndarray` of input `shape` where each value is a free parameter in the seach: https://github.com/rhayes777/PyAutoFit/pull/1021
- Name of `optimize` searches renamed to `mle`, for maximum likelihood estimator, with improvements to visualization: https://github.com/rhayes777/PyAutoFit/pull/1029
- Improvement to sensitivity mapping functionality and results: https://github.com/rhayes777/PyAutoFit/pulls?q=is%3Apr+is%3Aclosed
- More improvements to JAX Pytree interface, documentation still to come.

**PyAutoFit:**

- `Nautilus` now outputs results on the fly: https://github.com/rhayes777/PyAutoFit/pull/961
- Output latent samples of a model-fit, which are parameters derived from a model which may be marginalized over:

PR: https://github.com/rhayes777/PyAutoFit/pull/994
Example: https://github.com/Jammy2211/autofit_workspace/blob/release/notebooks/cookbooks/analysis.ipynb

- `model.info` file displays complex models in a more concise and readable way: https://github.com/rhayes777/PyAutoFit/pull/1012
- All samples with a weight below an input value are now removed from `samples.csv` to save hard disk space: https://github.com/rhayes777/PyAutoFit/pull/979
- Documentation describing autofit scientific workflow: https://github.com/rhayes777/PyAutoFit/pull/1011
- Refactor visualization into stand alone module: https://github.com/rhayes777/PyAutoFit/pull/995
- Refactor how results are returned after a search: https://github.com/rhayes777/PyAutoFit/pull/989
- Improved parallelism logging: https://github.com/rhayes777/PyAutoFit/pull/1009
- Likelihood consistency check now performed internally: https://github.com/rhayes777/PyAutoFit/pull/987
- Generation of initial search samples is now performed in parallel: https://github.com/rhayes777/PyAutoFit/pull/997
- No longer store `search_internal` on hard-disk. simplifying source code internals: https://github.com/rhayes777/PyAutoFit/pull/938
- Multiple small bug fixes and improvements to interface.

- Stability upgrades for change from .pickle to .json files.
- JAX implementation improved, still in development.
- Sensitivity mapping improvements.