Autolens

This is the latest version, which primarily brings in stability upgrades and fixes bugs.

This is a major release, which updates many aspects of the API, switches configuration files to YAML, requirements, etc.


**API Changes:**

- All elliptical light profiles and mass profiles no longer prefix with the `Ell` tag, for conciseness / readability. For example, `EllSersic` is now just `Sersic`, and `EllIsothermal` is now `Isothermal`.
- The `Sph` prefix is now a suffix, for example `SphSersic` is now `SersicSph` and `SphIsothermal` is now `Isothermal`.
- The ``elliptical_components` parameter has been shorted to `ell_comps`.
- The `ExternalShear` input has been changed from `elliptical_components` to `gamma_1` and `gamma_2` (the shear is still defined the same, where in the olversion version `elliptical_components[0] = gamma_2` and ` elliptical_components[1] = gamma_1`.
- The `manual_` API for data structures (e.g. `Array2D`, `Grid2D`) has been removed.


**Yaml Configs**

- Configuration files now support `.yaml`, which is provided with the autolens_workspace (https://github.com/Jammy2211/autolens_workspace/tree/release/config).
- The workspace configuration files are now fully documented,.


**Linear Light Profiles / Basis / Multi Gaussian Expansion**

Linear light profiles are now supported, which are identical to ordinary light profiles but the `intensity` parameter is solved for via linear algebra. This means lower dimensionality models can be fitted, making dynesty converge more reliably:

https://github.com/Jammy2211/autolens_workspace/blob/release/scripts/imaging/modeling/light_parametric_linear__mass_total__source_parametric_linear.py

Fits use a `Basis` object composed of many linear light profiles are supports, for example using a Multi Gaussian Expansion of 20+ Gaussians to fit the lens's light:

https://github.com/Jammy2211/autolens_workspace/blob/release/scripts/imaging/modeling/light_parametric_linear__mass_total__source_parametric_linear.py

These features are described fully in the following `HowToLens` tutorial:

https://github.com/Jammy2211/autolens_workspace/blob/release/scripts/howtolens/chapter_2_lens_modeling/tutorial_5_linear_profiles.py


**API Documentation**

API documentation on readthedocs is now being written, which is still a work in progress but more useable than it was previously (https://pyautolens.readthedocs.io/en/latest/api/data.html).


**SLaM V2**

The Source, Light and Mass (SLaM) pipelines have been updated to a version 2, which simplifies the pipelines and makes the API more concise (https://github.com/Jammy2211/autolens_workspace/tree/release/slam).


**Requirements**

The requirements of many projects have been updated to their latest versions, most notably `dynesty v2.0.2`.

- autolens_workspace now has `advanced` packages which make navigation simpler for new users to find beginner scritps.

- Redesign of position based lens mass model resampling. This feature now uses a likelihood penalty term based API, which includes a new default approach which traces (y,x) coordinates of multiple images from the image plane to the source plane and decreases the likelihood based on how far part in the source-plane they are (as opposed to resampling the mass model). See this doc for a full descritipon (https://pyautolens.readthedocs.io/en/latest/general/demagnified_solutions.html).

- If the position-based likelihood penalty term is not included in a fit using an `Inversion` (e.g. pixelized source reconstruction) an exception is raised, because the fit will likely cause a demagnified solution. This can be disabled manually (see https://pyautolens.readthedocs.io/en/latest/general/demagnified_solutions.html).

- LightProfileOperated objects implemented, which are already convolved with the imaging dataset's PSF for modeling point source components in a galaxy (see https://github.com/Jammy2211/autolens_workspace/blob/release/scripts/imaging/modeling/advanced/light_parametric_operated__mass_total__source_parametric.py).

- Numba is now an optional installation, see this doc page for a full description (https://pyautolens.readthedocs.io/en/latest/installation/numba.html).

- Starting point API for starting an MCMC fit with walkers in certain positions or maximum likelihood estimator fit with a start point implemented (https://github.com/rhayes777/PyAutoFit/pull/562). The example tutorial script for this feature is not written yet.

Multiwavelength lens modeling:

- https://pyautolens.readthedocs.io/en/latest/overview/overview_7_multi_wavelength.html
- https://github.com/Jammy2211/autolens_workspace/tree/release/notebooks/multi

Full Likelihood description notebook:

- https://github.com/Jammy2211/autolens_likelihood_function

**PyAutoGalaxy** full release:

- https://github.com/Jammy2211/PyAutoGalaxy

- Support for Python 3.9, 3.10.
- LogGaussianPrior implemented.
- Can output `Galaxy`, `Plane`, `Tracer` to and from json via `output_to_json` and `from_json` methods.

Added a step-by-step guide to the `log_likelihood_function`:

https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/imaging/modeling/log_likelihood_function/inversion.ipynb

Documentation showing how to analyze the results of a lens model fit now available on workspace:

https://github.com/Jammy2211/autolens_workspace/tree/release/notebooks/results