Autolens

The main updates are visualization of Delaunay mesh's using Delaunah triangles and a significant refactoring of over sampling, with the primary motivation to make the code much less complex for the ongoing JAX implementation.

There have also been more improvements to point source modeling, including JAX functionality, which will be documented fully in the near future.

What's Changed
* Feature/disable noise by Jammy2211 in https://github.com/Jammy2211/PyAutoLens/pull/324
* feature/delaunay_visual by Jammy2211 in https://github.com/Jammy2211/PyAutoLens/pull/323
* feature/inversion_noise_map by Jammy2211 in https://github.com/Jammy2211/PyAutoLens/pull/325
* feature/positions_lh_mass_centre by Jammy2211 in https://github.com/Jammy2211/PyAutoLens/pull/326
* feature/triangle array typing by rhayes777 in https://github.com/Jammy2211/PyAutoLens/pull/328
* feature/array testing by rhayes777 in https://github.com/Jammy2211/PyAutoLens/pull/327
* Feature/over sampling refactor by Jammy2211 in https://github.com/Jammy2211/PyAutoLens/pull/332
* remove max containing size from solver by rhayes777 in https://github.com/Jammy2211/PyAutoLens/pull/329
* feature/andrew implementation by rhayes777 in https://github.com/Jammy2211/PyAutoLens/pull/331


**Full Changelog**: https://github.com/Jammy2211/PyAutoLens/compare/2024.11.13.2...2025.1.18.7

Small bug fixes and optimizations for Euclid lens modeling pipeline.

Minor release with stability updates and one main feature.

- Extra Galaxies API for modeling multiple galaxies at once: https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/features/extra_galaxies.ipynb

- Multiwavelength lens modeling with SLaM multi wavelength pipelines: https://github.com/Jammy2211/autolens_workspace/tree/main/scripts/advanced/chaining/slam/multi

- More improvements to Point source solver and Shape solver.

- Sensitivity mapping improvements which will be fully documented in the future.

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
https://github.com/Jammy2211/PyAutoGalaxy/blob/main/requirements.txt
https://github.com/Jammy2211/PyAutoGalaxy/blob/main/optional_requirements.txt
https://github.com/Jammy2211/PyAutoLens/blob/main/requirements.txt
https://github.com/Jammy2211/PyAutoLens/blob/main/optional_requirements.txt

**Workspace Restructure:**

This release has a workspace restructure, which is now grouped at a high level by tasks (e.g. `modeling`, `simulators`) rather than datasets:

https://github.com/Jammy2211/autolens_workspace

The readthedocs have been greatly simplified and include a **new user guide** to help navigate the new workspace:

https://pyautolens.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html

**PyAutoLens:**

- Point source modeling significantly improved with triangle tracing method, image plane chi squared supported: https://github.com/Jammy2211/autolens_workspace/tree/release/notebooks/modeling/point_source
- Shape based point-source modeling for magnification calculations: https://github.com/Jammy2211/PyAutoLens/pull/300
- Improved Cosmology wrapper to support new `astropy` and easier to use in models: https://github.com/Jammy2211/PyAutoGalaxy/pull/193
- Ellipse Fitting: https://github.com/Jammy2211/autogalaxy_workspace/tree/release/notebooks/advanced/misc/ellipse


**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.

**PyAutoGalaxy / PyAutoLens:**

- Remove `Plane` object and replace with `Galaxies` object
- Shapelets improvements: https://github.com/Jammy2211/PyAutoGalaxy/pull/173
- Adaptive over sampling of grids for a pixelization: https://github.com/Jammy2211/PyAutoGalaxy/pull/168
- `BasisPlotter` which plots each basis (e.g. each Gaussian of an MGE): https://github.com/Jammy2211/PyAutoGalaxy/pull/173
- Plot mappings between source and image plane of a pixelization as lines: https://github.com/Jammy2211/PyAutoGalaxy/pull/172
- For multi-wavelength datasets model offsets between each dataset: https://github.com/Jammy2211/PyAutoGalaxy/pull/171
- Modeling of background sky: https://github.com/Jammy2211/PyAutoGalaxy/pull/170
- Improvements to use of adapt images for adaptive pixelizations: https://github.com/Jammy2211/PyAutoGalaxy/pull/160
- Improved angle conversions for computing errors on mass profile and shear angles from `ell_comps`: https://github.com/Jammy2211/PyAutoGalaxy/pull/169
- Remove `sub_size` from all classes (e.g. `Array2D`, `Mask2D`) to simplify API.
- `MaternKernel` added: https://github.com/Jammy2211/PyAutoGalaxy/pull/148
- Refactor of tracer module: https://github.com/Jammy2211/PyAutoLens/pull/255

- Log10 plots implemented in 1D and 2D, which show certain quantities (e.g. galaxy convergence) more clear and include contours showing log10 values:


- Improved subplots including addition of log10 panels:


- `Pixelization` API now has separate entry for an `image_mesh`, defining how the source pixel centres are computed (E.g. using a KMeans clustering) and the `mesh` is now just the method (e.g. `Delaunay`):


pixelization = al.Pixelization(
image_mesh=al.image_mesh.Overlay(shape=(25, 25)),
mesh=al.mesh.Delaunay(),
regularization=al.reg.Constant(coefficient=1.0),
)


- Implemented `Hilbert` image-mesh which is a significant improvement on `KMeans` clustering for creating the distribution of source pixels for a pixelization and inversion.

- Simplified `adapt_dataset` API to now only pass via an `AdaptImage` class, which is not passed as `Galaxy` attributes anymore but instead through the `FitImaging` object.

- Removed `SetupAdapt` object and pass `image_mesh_pixels` as an integer through pipelines.

- Added Exponential / Gaussian smoothing kernels for regularization documented in Vernardos 2022 (https://arxiv.org/abs/2202.09378)