epic: expand autogalaxy_workspace_test to mirror autolens_workspace_test coverage

[Jammy2211]

Overview

autogalaxy_workspace_test is currently very sparse — only scripts/aggregator/ exists, and there
is no GitHub Actions CI. This epic tracks nine discrete sub-tasks that together bring it up to the
coverage autolens_workspace_test already provides: a smoke-test CI, model_composition/,
jax_likelihood_functions/{imaging,interferometer,multi}/, jax_grad/{imaging,interferometer,multi}/,
and a minimal imaging/ suite. Each sub-task has a prompt file in
admin_jammy/prompt/autogalaxy/ and ships as its own PR.

Sub-tasks

• 1. CI setup (blocker for 2–9) — admin_jammy/prompt/autogalaxy/autogalaxy_workspace_test_ci.md
• 2. scripts/model_composition/ — autogalaxy_workspace_test_model_composition.md (shipped via PR feat: scripts/model_composition/multi_galaxy_mge.py port (task 2/9) #27)
• 3. scripts/jax_likelihood_functions/imaging/ — autogalaxy_workspace_test_jax_likelihood_imaging.md (includes PyAutoGalaxy pytree registration scaffold)
• 4. scripts/jax_likelihood_functions/interferometer/ — autogalaxy_workspace_test_jax_likelihood_interferometer.md (shipped via PR feat: jax_likelihood_functions/interferometer/ port #17)
• 5. scripts/jax_likelihood_functions/multi/ — autogalaxy_workspace_test_jax_likelihood_multi.md (shipped via PR feat: jax_likelihood_functions/multi/ port #19)
• 6. scripts/jax_grad/imaging/ — autogalaxy_workspace_test_jax_grad_imaging.md (shipped via PR feat: scripts/jax_grad/imaging/ — lp.py + mge.py port (task 6/9) #29)
• 7. scripts/jax_grad/interferometer/ — autogalaxy_workspace_test_jax_grad_interferometer.md (shipped via PR feat: scripts/jax_grad/interferometer/ — lp.py + mge.py from scratch (task 7/9) #31)
• 8. scripts/jax_grad/multi/ — autogalaxy_workspace_test_jax_grad_multi.md (shipped via PR feat: scripts/jax_grad/multi/ — lp.py + mge.py from scratch (task 8/9, epic-final) #33)
• 9. scripts/imaging/ (model_fit + 3 visualization scripts) — autogalaxy_workspace_test_imaging.md (shipped via PR feat: scripts/imaging/ — model_fit + visualization + JIT visualizer scripts #11)

Key cross-cutting risk

Tasks 3–9 depend on pytree registration on PyAutoGalaxy's analysis classes. Today,
autogalaxy/imaging/model/analysis.py and autogalaxy/interferometer/model/analysis.py have
no _register_fit_imaging_pytrees / equivalent — autolens has these, autogalaxy does not.
The JAX sub-tasks will need library PRs on PyAutoGalaxy before their workspace PRs can land.
Each sub-prompt flags this as a spawn-off.

Exclusions across all sub-tasks: no *_dspl.py ports (double-source-plane is lens-specific).

Original prompt

Click to expand starting prompt

The autogalaxy_workspace_test is very light compared to autolens_workspacd_test in terms of its script
and it does not have a .github actions continuous integration. Therefore, plan the following work as a series
of prompts in this folder, run them one after another as seaprate agent tasks:

• Set up contiuous integration server on autogalaxy_workspace_test
• Set up folder `scripts/model_composition` and set up autogalaxy version of existing scripts.
• Set up folder `scripts/jax_likelihood_functions/imaging` and set up autogalaxy versions of all examples (dont do dspl). This will likely require some spawn-off tasks which do pytree registration so make sure this prompt looks at our recent pytree work).
• Do same for `scripts/jax_likelihood_functions/interferometer`.
• Do same for `scripts/jax_likelihood_functions/multi`.
• Set up folder `scripts/jax_grad/imaging` and set up autogalaxy versions of all examples (dont do dspl). This will likely require some spawn-off tasks which do pytree registration so make sure this prompt looks at our recent pytree work).
• Do same for `scripts/jax_grad/interferometer`.
• Do same for `scripts/jax_grad/multi`.
• Set up a `scripts/imaging` folder like autolens_workspace_test's, but only include model_fit.py, modeling_visualization_jit.py, visualization.py, visualization_jax.py