v2026.6.26.642

PyAutoLens v2026.6.26.642

No direct changes in this release.

Upstream Changes

PyAutoArray

• Add optional arcsecond double-prime tick labels (#350)

---

Full changelog: 2026.6.25.641...2026.6.26.642

v2026.6.25.641

PyAutoLens v2026.6.25.641

What's New

Breaking Changes

• feat: datacube shared-state for AnalysisInterferometer via curvature preloads (#566)
• Honour PYAUTO_TEST_MODE in LOSSampler to fix los_halos simulator timeouts (#559)
  • autolens.lens.los.negative_kappa_from gains two optional keyword arguments, quad_limit=50 and quad_epsrel=1.49e-8 (both scipy's own quad defaults), threaded into its inner and outer integrals. Existing callers are unaffected. LOSSampler.galaxies_from now reads autoconf.test_mode.is_test_mode() internally; its signature is unchanged. No removals or renames. See full details below.

New Features

• docs: add signpost llms.txt + consolidate agent instructions into AGENTS.md (#570)
• test: regression guard for HowToLens tutorial_3 NaN axis-limits crash (#560)

Bug Fixes

• fix(jax): defensive pytree dedup in imaging/interferometer analyses (#561)

Internal

• main.yml → thin caller to Pulse reusable lib-tests (Stage 4 Phase A) (#572)
• Remove url_check.yml: URL hygiene centralised in PyAutoPulse (#571)
• docs: consolidate agent instructions into canonical AGENTS.md (#569)
• refactor(latent): LatentLens class + declare Analysis.Latent (Phase 2) (#568)
• Feature/positions threshold (#507)

Upstream Changes

PyAutoFit

• main.yml → thin caller to Pulse reusable lib-tests (Stage 4 Phase A) (#1322)
• Remove url_check.yml: URL hygiene centralised in PyAutoPulse (#1321)
• docs: add signpost llms.txt + consolidate agent instructions into AGENTS.md (#1320)
• docs: consolidate agent instructions into canonical AGENTS.md (#1319)
• refactor(latent): migrate af.ex.Analysis + cookbook docs to the Latent class (#1318)
• fix: skip latent computation without keys (#1317)
• refactor(latent): first-class Latent class + engine extraction (Phase 1) (#1315)
• fix: expand bypass-mode fake samples (#1314)
• test: skip NSS tests without optional dependency (#1312)
• fix(latent): degenerate latent edge cases (quantile n=1, latent exceptions, anti-correlated NaNs) (#1311)
• fix(latent): global masking in compute_latent_samples to prevent KeyError on per-batch NaN drops (#1310)
• feat: cross-Analysis shared per-evaluation state in FactorGraphModel (#1308)
• chore(deps): allow anesthetic>=2.9.0 to unblock jax>=0.7 / numpy>=2 resolution (#1306)
• fix(nss): chunked algo.init follow-up to #1303 (#1305)
• feat(nss): chunk_size kwarg for inversion-heavy A100 likelihoods (#1303)
• fix(jax): structural defense against cached_property pytree/dict leaks (#1302)

PyAutoArray

• main.yml → thin caller to Pulse reusable lib-tests (Stage 4 Phase A) (#349)
• Remove url_check.yml: URL hygiene centralised in PyAutoPulse (#348)
• docs: add signpost llms.txt + consolidate agent instructions into AGENTS.md (#347)
• docs: consolidate agent instructions into canonical AGENTS.md (#346)
• feat: Preloads API for reusing channel-invariant inversion quantities (#344)
• fix(jax): exclude cached_property descriptors from pytree flatten paths (#343)

PyAutoGalaxy

• main.yml → thin caller to Pulse reusable lib-tests (Stage 4 Phase A) (#476)
• Remove url_check.yml: URL hygiene centralised in PyAutoPulse (#475)
• docs: add signpost llms.txt + consolidate agent instructions into AGENTS.md (#474)
• docs: consolidate agent instructions into canonical AGENTS.md (#473)
• refactor(latent): LatentGalaxy class + declare Analysis.Latent (Phase 2) (#472)
• Lensing potential for elliptical/spherical dark-matter profiles (NFW/gNFW) + NFWSph fix (#470)
• fix(jax): defensive pytree dedup in imaging/interferometer analyses (#468)
• fix(mass): convergence_func on PowerLawBroken, PowerLawMultipole, cNFW family (#467)

---

Full changelog: 2026.5.29.4...2026.6.25.641

v2026.5.29.4

PyAutoLens v2026.5.29.4

What's New

Breaking Changes

• Honour PYAUTO_TEST_MODE in LOSSampler to fix los_halos simulator timeouts (#559)
  • autolens.lens.los.negative_kappa_from gains two optional keyword arguments, quad_limit=50 and quad_epsrel=1.49e-8 (both scipy's own quad defaults), threaded into its inner and outer integrals. Existing callers are unaffected. LOSSampler.galaxies_from now reads autoconf.test_mode.is_test_mode() internally; its signature is unchanged. No removals or renames. See full details below.
• fix: effective_einstein_radius falls back to NumPy when jax_zero_contour missing (#558)
  • Behaviour change (no signature change): on the JAX path (xp is not np), effective_einstein_radius now detects whether jax_zero_contour is importable. If yes — unchanged JIT path. If no — falls through to the existing NumPy einstein_radius_from(grid) branch with a one-time-per-process warning. NumPy callers are unaffected. New private helper _jax_zero_contour_available and module-level flag _JAX_ZERO_CONTOUR_FALLBACK_WARNED.
• fix: raw-flux latents + soft-fail magzero-required µJy (#557)
• feat: first-class lensing latent variable API in PyAutoLens (#534)
  • New public module autolens.analysis.latent exposing the five latent functions + LATENT_FUNCTIONS registry + latent_keys_enabled() reader. AnalysisImaging gains LATENT_KEYS @property and compute_latent_variables(parameters, model). New autolens/config/latent.yaml (all keys default false). Helpers ab_mag_via_flux_from / flux_mujy_via_ab_mag_from are imported from autogalaxy.imaging.model.latent (shipped in PyAutoGalaxy #441). No PyAutoFit changes. Latents take a generic fit argument and use APIs shared between FitImaging and FitInterferometer, so a future AnalysisInterferometer wiring can reuse the registry without duplication.
• fix(viz): make _compute_critical_curve_lines failures loud, not silent (#527)
  • _compute_critical_curve_lines is a private helper — no public API surface changes. Behavioural change: unexpected exceptions now emit a WARNING log with traceback before falling back to no-overlay rendering, instead of being silently swallowed.

New Features

• test: regression guard for HowToLens tutorial_3 NaN axis-limits crash (#560)
• Add placeholder subplot_fit_quick for weak lensing and combined fits (#553)
• Add subplot_fit_quick for point source quick updates (#552)
• Simplify subplot_fit_quick: use fit properties directly (#551)
• Add subplot_fit_quick for interferometer quick updates (#549)
• perf: cache expensive @Property on Fit classes (#548)
• Add subplot_fit_quick for faster quick-update rendering (#546)
• feat: SimulatorInterferometer.via_tracer_from auto-default xp from parent use_jax (#540)
• feat: SimulatorImaging.via_tracer_from auto-default xp from parent use_jax (#539)
• feat: PointSolver(use_jax=True) + autolens.jax.register_tracer_classes (#538)

Bug Fixes

• fix(jax): defensive pytree dedup in imaging/interferometer analyses (#561)
• test: lock down WeakDataset json round-trip (paired with PyAutoArray fix) (#555)
• Fix subplot_fit_quick styling: arcsecond axes, source plane, code reuse (#550)

Internal

• Fast subplot_fit_quick: sub-second rendering for quick updates (#547)
• feat: batched_simulate_substructure via jax.vmap (#545)
• feat: simulate_substructure end-to-end jittable simulator (#544)
• feat: scan-based multi-plane ray-tracing for substructure (#543)
• fix: total_source_flux_mujy wrong value for linear light profiles (#536)
• docs: add autolens_assistant prototype callout to README and docs index (#530)
• refactor(model_util): replace simulator_start_here_model_from with direct random_galaxies_for_simulation_from (#529)
• refactor: archive quantity package to autolens_workspace_developer/legacy (#528)

Upstream Changes

PyAutoFit

• chore(deps): allow anesthetic>=2.9.0 to unblock jax>=0.7 / numpy>=2 resolution (#1306)
• fix(nss): chunked algo.init follow-up to #1303 (#1305)
• feat(nss): chunk_size kwarg for inversion-heavy A100 likelihoods (#1303)
• fix(jax): structural defense against cached_property pytree/dict leaks (#1302)
• fix(jax): keep parameterization cache off ModelInstance + auto-register pytrees (#1300)
• Cache model.parameterization; try interactive matplotlib backends (#1299)
• Prefer fit_quick.png in quick-update display candidates (#1298)
• Remove use_jax_for_visualization; add visualization warmup (#1297)
• fix: skip _compute_latent_samples in PYAUTO_TEST_MODE (#1294) (#1295)
• Add live_visual_update flag for opt-in on-the-fly visualization (#1293)
• fix: PYAUTO_TEST_MODE should write to a separate output dir (#1292)
• feat(quick_update): IPython.display.update_display for live Jupyter cells (#1290)
• feat(analysis): LATENT_BATCH_MODE attribute (vmap default, jit option) (#1288)
• Fix Sample.kwargs mixed string/tuple key bug (#1287)
• nss extras: strip git+https URLs to unblock PyPI uploads (#1286)

PyAutoArray

• fix(jax): exclude cached_property descriptors from pytree flatten paths (#343)
• fix: VectorYX2DIrregular from_dict round-trip (missing values property) (#342)
• perf: cache expensive @Property on Fit classes (#341)
• fix: make Array2D.native jit-traceable for JAX simulator path (#339)
• fix: raise ValueError on xp=np + jnp-backed-grid mismatch (#337)
• feat: SimulatorInterferometer(use_jax=True) + xp-aware preprocess Gaussian noise (#336)
• feat: SimulatorImaging(use_jax=True) + xp-aware preprocess noise (#335)
• TransformerNUFFT: add chunk_size knob to cap nufftax gather buffer (#330)
• interferometer: enable sparse_operator for nufftax TransformerNUFFT (#329)

PyAutoGalaxy

• fix(jax): defensive pytree dedup in imaging/interferometer analyses (#468)
• fix(mass): convergence_func on PowerLawBroken, PowerLawMultipole, cNFW family (#467)
• fix(mass): wire convergence_func on dPIE family for MGE decomposition (#466)
• fix: soft-fail jax_zero_contour callers in lens_calc to NaN/[] (#465)
• fix: raw-flux latent + soft-fail magzero-required µJy (#463)
• perf: cache expensive @Property on Fit classes (#462)
• perf: vectorize MGE potential over components (#461)
• fix: elliptical MGE potential via deflection line integral (#460)
• fix: use xp.sqrt in NFWSph.potential_func_sph (#458)
• fix: add xp=np to convergence_func across all mass profiles (#457)
• feat: vmapped_deflections_from for batched subhalo deflections (#455)
• fix: cNFWSph deflection boundary bug and MCR validation (#451) (#454)
• docs: LaTeX docstrings for all mass profile classes (#453)
• feat: MGE/CSE fallback for zero-retu...

v2026.5.21.1

PyAutoLens v2026.5.21.1

What's New

Breaking Changes

• docs(api): sync mass.rst with full al.mp namespace + lmp / lmp_linear (#520)
• feat: redesign subplot_fit panels — add Source Plane (Mid Zoom) (#518)
  • • _plot_source_plane(...) and plane_image_from(...) gain a zoom_extent_scale kwarg. plane_image_from also gains a zoom_extent_bounds kwarg.
  • • subplot_fit and subplot_fit_log10 produce the new 12-panel layout — same panel count, different ordering, one renamed panel ("Source Plane (Zoomed)" → "Source Plane (Max Zoom)"), one new panel ("Source Plane (Mid Zoom)"), one removed panel ("Data (Source Scale)").
• docs(api): sync light profile reference with PyAutoGalaxy (#516)
• fix: AnalysisPoint.init kwargs passthrough (#506)
  • al.AnalysisPoint.__init__ gains a **kwargs passthrough — strictly additive. Any caller that previously worked is unaffected. New: callers can now pass use_jax_for_visualization=True (or any other kwarg accepted by the autofit base Analysis) without TypeError.

New Features

• feat: re-export galaxy_model_csv helpers under al.* (#526)
• feat(weak): FitWeak class + plotters (#524) (#525)
• feat(weak): aplt plotters for WeakDataset shear catalogues (#496) (#523)
• docs(api): list SersicMultipole and GaussianMultipole in autosummary (#515)

Bug Fixes

• docs: audit-driven URL fixes across docs, READMEs, and docstrings (#509)

Internal

• feat(AnalysisImaging): plumb dataset_model into adapt_images_via_instance_from (#512)
• ci: add live URL audit (weekly cron) + grandfather current broken URLs (#510)
• added maximum threshold (#505)

Upstream Changes

PyAutoFit

• nss extras: strip git+https URLs to unblock PyPI uploads (#1286)
• perf: direct-ndtr fast path for TruncatedGaussianPrior.value_for (#1285)
• fix: coerce figure_of_metric return to Python float for Drawer + JAX (#1283)
• ci: split NSS tests into parallel job (handley-lab blackjax fork ≠ mainline) (#1281)
• revert: default use_jax_for_visualization to False (reverts #1278) (#1280)
• feat: default use_jax_for_visualization to follow use_jax in Analysis.init (#1278)
• feat: autofit[nss] install extra (Phase 4 of nss_first_class_sampler) (#1277)
• feat: af.NSS checkpoint/resume + on-the-fly visualization (Phases 2-3) (#1274)
• feat: af.NSS NonLinearSearch wrapper for Nested Slice Sampling (Phase 1 of nss_first_class_sampler) (#1272)
• fix: dedupe number_of_cores in Drawer for from_dict round-trip (#1270)
• fix: log_prior_from_value sign convention — density form across Prior subclasses (#1269)
• ci: add live URL audit (weekly cron) + grandfather current broken URLs (#1268)
• fix: add quick_update kwarg to VisualizerExample.visualize_combined (#1267)
• docs: audit-driven URL fixes across docs, READMEs, and docstrings (#1265)
• Disable model.graph output by default (#1264)
• feat: JAX-native priors — xp dispatch on value_for / log_prior_from_value / vector_from_unit_vector (#1263)
• fix: exclude exclude_identifier_fields attrs from model.info (#1261)

PyAutoArray

• Pin nufftax >=0.4.0,<0.5.0 on Python 3.12+ (#328)
• feat(grids): add respect_small_datasets kwarg to Grid2D.uniform (#327)
• fix(mask): cap radius under PYAUTO_SMALL_DATASETS (#325)
• feat: add zoom_extent_scale to Mapper.extent_from for Mid Zoom panel (#324)
• feat: RectangularRotatedAdaptImage — PCA rotation fixes multi-source ghost-peak failure (#323)
• fix(inversion): make AbstractMeshGeometry picklable (xp module → _use_jax bool + property) (#321)
• Reduce critical curves and caustics overlay linewidth from 2 to 1 (#319)
• Add KNNBarycentric mesh: JAX-native Delaunay-class interpolator (#318)
• fix(interferometer): correct sparse curvature for Pmax > 1 (Delaunay) (#316)
• fix(interferometer-sparse): guard against Delaunay mappers (issue #314) (#315)
• fix(hilbert): support offset-centre circular masks (#313)
• feat(DatasetModel): add grid_rotation_angle for multi-band rotation (#312)
• feat(interferometer): from_fits accepts raise_error_dft_visibilities_limit (#311)
• ci: add live URL audit (weekly cron) + grandfather current broken URLs (#310)
• docs: audit-driven URL fixes across docs, READMEs, and docstrings (#309)
• feat: add aa.interp_2d (NumPy + JAX bilinear interpolation) (#308)

PyAutoGalaxy

• Pin jax_zero_contour >=2.0.0,<3.0.0 in [jax] extras (#432)
• fix(lens_calc): preserve evaluation_grid extent under PYAUTO_SMALL_DATASETS=1 (#431)
• fix: handle r=0 in NFWSph deflections (#430)
• fix(csv): preserve TuplePrior on af.Model built from tuple-param rows (#429)
• feat(galaxy): named-galaxy CSV reader/writer for full model round-trips (#428)
• fix: EllipseMultipoleScaled JAX-traceable via deferred derivation (#427)
• fix: Basis.image_2d_from and dPIEPotential.convergence_2d_from return wrong wrapper types (#425)
• config: add prior defaults for ExternalPotential (#423)
• feat(mass): add ExternalPotential mass profile (Powell 2022 Eq 4) (#422)
• refactor(light): split multipole module + add ag.lp_linear variants (#421)
• feat(light): add SersicMultipole and GaussianMultipole profiles (#420)
• feat(AdaptImages): rotate cached mesh grid with DatasetModel transforms (#416)
• ci: add live URL audit (weekly cron) + grandfather current broken URLs (#415)
• fix: add quick_update kwarg to VisualizerImaging.visualize_combined (#414)
• docs: audit-driven URL fixes across docs, READMEs, and docstrings (#413)
• feat: AnalysisEllipse.fit_from + JAX pytree registration (keystone) (#412)
• refactor: unify FitEllipse perimeter sampling; add JAX support (#410)
• refactor: parameterise Ellipse + EllipseMultipole math on xp (#408)
• feat: replace Ludlow16 colossus pure_callback with JAX-native impl (#403) (#406)
• fix: register DatasetModel pytree in _register_fit_quantity_pytrees (#405)
• feat: wire ag.VisualizerQuantity through fit_for_visualization (#404)
• docs(research): Ludlow16 JAX concentration feasibility study (#397) (#402)
• feat: pytree registration for FitEllipse + FitQuantity (Phase 0c) (#401)
• fix: ag.AnalysisInterferometer.init kwargs passthrough (#399)
• refactor: DatasetInterp delegates to aa.interp_2d; expose xp (#398)

---

Full changelog: https://github.com/PyAutoLabs/PyAutoLens/co...

v2026.5.14.2

PyAutoLens v2026.5.14.2

What's New

Breaking Changes

• fix: AnalysisPoint.init kwargs passthrough (#506)
  • al.AnalysisPoint.__init__ gains a **kwargs passthrough — strictly additive. Any caller that previously worked is unaffected. New: callers can now pass use_jax_for_visualization=True (or any other kwarg accepted by the autofit base Analysis) without TypeError.
• feat: re-export galaxy_table CSV helpers from autogalaxy (#502)
  • Three new namespace exports on autolens, all pointing at the autogalaxy implementations from PyAutoGalaxy#392:
  • • al.GalaxyTable
• fix: AnalysisInterferometer.init kwargs passthrough (#500)
  • al.AnalysisInterferometer.__init__ gains a **kwargs passthrough — strictly additive. Any caller that previously worked is unaffected. New: callers can now pass use_jax_for_visualization=True (or any other kwarg accepted by the autofit base Analysis) without TypeError.

New Features

• docs: add nufftax + FINUFFT citation guidance (#503)

Bug Fixes

• fix: AnalysisImaging.log_likelihood_function CPU branch returns figure_of_merit (not log_likelihood) (#504)

Internal

• feat: re-export TransformerNUFFTPyNUFFT (legacy pynufft NUFFT) (#501)
• fix: tracer_util JAX-safe for traced subhalo redshifts (#498) (#499)

Upstream Changes

PyAutoFit

• fix: populate NUTS samples_info keys under test-mode bypass (#1260)
• fix: stop passing dataset=None to fit_cls when sensitivity Job is complete (#1259)

PyAutoArray

• feat: add aa.interp_2d (NumPy + JAX bilinear interpolation) (#308)
• perf: batched transform_mapping_matrix in TransformerNUFFT (single nufft2d2 call) (#305)
• fix(inversion): regularization_weights_mapper_dict uses correct linear_obj_list index (#304)
• feat: nufftax-backed TransformerNUFFT as default; rename pynufft variant to TransformerNUFFTPyNUFFT (#303)
• Make use_mixed_precision actually emit fp32 FFT for light profiles (#302)
• feat: honor PYAUTO_SMALL_DATASETS in Imaging.from_fits (#301)

PyAutoGalaxy

• feat: replace Ludlow16 colossus pure_callback with JAX-native impl (#403) (#406)
• fix: register DatasetModel pytree in _register_fit_quantity_pytrees (#405)
• feat: wire ag.VisualizerQuantity through fit_for_visualization (#404)
• docs(research): Ludlow16 JAX concentration feasibility study (#397) (#402)
• feat: pytree registration for FitEllipse + FitQuantity (Phase 0c) (#401)
• fix: ag.AnalysisInterferometer.init kwargs passthrough (#399)
• refactor: DatasetInterp delegates to aa.interp_2d; expose xp (#398)
• docs: add nufftax + FINUFFT citation guidance (#396)
• test: pin FitEllipse masked-points-loop behaviour (#395)
• feat: add galaxy_table CSV reader/writer for galaxy populations (#393)
• feat: re-export TransformerNUFFTPyNUFFT (legacy pynufft NUFFT) (#391)
• feat: dispatch autogalaxy visualizers via fit_for_visualization (#390)

---

Full changelog: 2026.5.8.2...2026.5.14.2

v2026.5.8.2

⚠️ v2026.5.8.2 is a no-op re-release of v2026.5.8.1 — same code, second release dispatched the same day to validate updated release-pipeline gates. The full set of changes shipped on 2026-05-08 follows.

PyAutoLens v2026.5.8.2

What's New

Breaking Changes

• Add VisualizerInterferometer combined plotter for datacube fits (#494)
• fix: synthetic PositionsLH under skip_checks + test_mode (#490)
• feat(weak-lensing): add WeakDataset + SimulatorShearYX (step 1) (#473)

Internal

• fix: tracer_util JAX-safe for traced subhalo redshifts (#498) (#499)
• refactor: replace os.path with pathlib (#497)
• docs: update workspace prose refs from README.rst to README.md (#493)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#492)
• Fix mapper-index lookup in source_plane_inversion_centre_from (#491)
• test: move sparse-operator parity check to autolens_workspace_test (#489)
• test: clean up jax false positives in test_autolens/ (#488)
• docs: convert prose .rst files to MyST .md (#487)

Upstream Changes

PyAutoFit

• fix: populate NUTS samples_info keys under test-mode bypass (#1260)
• fix: stop passing dataset=None to fit_cls when sensitivity Job is complete (#1259)
• refactor: replace os.path with pathlib (#1258)
• feat: add BlackJAXNUTS first-class non-linear search (#1256)
• Visualizer.visualize_combined: accept quick_update kwarg (#1254)
• Fix AnalysisFactor.visualize_combined dispatch in FactorGraph (#1253)
• Refresh cached SearchUpdater when AbstractSearch.paths is reassigned (#1252)
• docs: update workspace prose refs from README.rst to README.md (#1251)
• Support fixed Array elements through the EP fitting pipeline (#1250)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#1249)
• Add EPAnalysisFactor for cavity-message injection (#1248)
• test: delete jax-using unit tests (moved to autofit_workspace_test) (#1247)
• docs: convert prose .rst files to MyST .md (#1246)

PyAutoArray

• feat: honor PYAUTO_SMALL_DATASETS in Imaging.from_fits (#301)
• refactor: replace os.path with pathlib (#300)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#298)
• Fix subplot_of_mapper crash on interferometer data_subtracted (#297)
• fix OOB read in psf_precision_value_from causing NaN sparse-CPU log_evidence (#296)
• test: remove jax-using unit tests; assertions moved to autolens_workspace_test (#295)
• docs: convert index.rst to MyST .md (#294)

PyAutoGalaxy

• refactor: replace os.path with pathlib (#388)
• docs: update workspace prose refs from README.rst to README.md (#387)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#386)
• fix: xp-gate jax.scipy.special.factorial in shapelets/exponential.py (#385)
• test: remove jax from unit tests (moved to autogalaxy_workspace_test) (#384)
• docs: convert prose .rst files to MyST .md (#383)

---

Full changelog: 2026.5.1.4...2026.5.8.2

v2026.5.8.1

PyAutoLens v2026.5.8.1

What's New

Breaking Changes

• Add VisualizerInterferometer combined plotter for datacube fits (#494)
• fix: synthetic PositionsLH under skip_checks + test_mode (#490)
• feat(weak-lensing): add WeakDataset + SimulatorShearYX (step 1) (#473)

Internal

• fix: tracer_util JAX-safe for traced subhalo redshifts (#498) (#499)
• refactor: replace os.path with pathlib (#497)
• docs: update workspace prose refs from README.rst to README.md (#493)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#492)
• Fix mapper-index lookup in source_plane_inversion_centre_from (#491)
• test: move sparse-operator parity check to autolens_workspace_test (#489)
• test: clean up jax false positives in test_autolens/ (#488)
• docs: convert prose .rst files to MyST .md (#487)

Upstream Changes

PyAutoFit

• fix: populate NUTS samples_info keys under test-mode bypass (#1260)
• fix: stop passing dataset=None to fit_cls when sensitivity Job is complete (#1259)
• refactor: replace os.path with pathlib (#1258)
• feat: add BlackJAXNUTS first-class non-linear search (#1256)
• Visualizer.visualize_combined: accept quick_update kwarg (#1254)
• Fix AnalysisFactor.visualize_combined dispatch in FactorGraph (#1253)
• Refresh cached SearchUpdater when AbstractSearch.paths is reassigned (#1252)
• docs: update workspace prose refs from README.rst to README.md (#1251)
• Support fixed Array elements through the EP fitting pipeline (#1250)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#1249)
• Add EPAnalysisFactor for cavity-message injection (#1248)
• test: delete jax-using unit tests (moved to autofit_workspace_test) (#1247)
• docs: convert prose .rst files to MyST .md (#1246)

PyAutoArray

• feat: honor PYAUTO_SMALL_DATASETS in Imaging.from_fits (#301)
• refactor: replace os.path with pathlib (#300)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#298)
• Fix subplot_of_mapper crash on interferometer data_subtracted (#297)
• fix OOB read in psf_precision_value_from causing NaN sparse-CPU log_evidence (#296)
• test: remove jax-using unit tests; assertions moved to autolens_workspace_test (#295)
• docs: convert index.rst to MyST .md (#294)

PyAutoGalaxy

• refactor: replace os.path with pathlib (#388)
• docs: update workspace prose refs from README.rst to README.md (#387)
• docs: convert remaining prose .rst to MyST .md (pass 2) (#386)
• fix: xp-gate jax.scipy.special.factorial in shapelets/exponential.py (#385)
• test: remove jax from unit tests (moved to autogalaxy_workspace_test) (#384)
• docs: convert prose .rst files to MyST .md (#383)

---

Full changelog: 2026.5.1.4...2026.5.8.1

v2026.5.1.4

PyAutoLens v2026.5.1.4

Highlights

Python 3.9–3.13 supported, 3.12 / 3.13 recommended

This release expands supported Python versions to 3.9 through 3.13 (#486). 3.12 and 3.13 are first-class recommended; 3.9, 3.10, 3.11 are supported but emit a loud (bypassable) banner on import. Silence the banner via version.python_version_check: False in your workspace's config/general.yaml. Python 3.14 is not yet supported.

Key impacts for users:

• requires-python = ">=3.9" in pyproject.toml (lower floor than before)
• Classifiers now cover 3.9, 3.10, 3.11, 3.12, 3.13
• JAX is now an optional extra: pip install autolens[jax], gated on python_version >= '3.11'. Plain pip install autolens no longer pulls JAX as a transitive dep.

HowToLens moved to its own repo

The HowToLens lecture series now lives in its own repository at PyAutoLabs/HowToLens (#468). Existing URLs/prose in the library and workspace pointing at the previous location have been updated. Clone the new repo to follow the tutorial chapters.

Performance

• Short-circuit set_snr_of_snr_light_profiles when no SNR profiles are present (#471) — eliminates a redundant traversal in models that don't use SNR-tuned profiles

Internal / Cleanup

• Remove unused pyprojroot import (#485)
• Add mask padding likelihood sanity check to test suite (#436)
• Clean up jax false positives in test_autolens/ (#488)
• Move sparse-operator parity check to autolens_workspace_test (#489) — keeps the library's unit suite numpy-only

Upstream Changes

PyAutoConf

• Support Python 3.9–3.13, first-class 3.12/3.13 (PyAutoConf#102)
• Soften Python version check with general.yaml bypass (PyAutoConf#96)

PyAutoArray

• Support Python 3.9–3.13 (PyAutoArray#293)
• Handle off-centre masks in convolver and blurring grid padding (PyAutoArray#274)
• Fix NaN gradients from jaxnnls backward pass via Jacobi preconditioning (PyAutoArray#279)
• Lower nnls_target_kappa default to 1e-11 for stable NNLS gradients (PyAutoArray#283, #284)

PyAutoFit

• Support Python 3.9–3.13 (PyAutoFit#1244)
• JAX-jitted likelihoods in Dynesty via use_jax_jit (PyAutoFit#1243)
• Skip FitException samples in compute_latent_samples (PyAutoFit#1233)

PyAutoGalaxy

• Support Python 3.9–3.13 (PyAutoGalaxy#382)
• Mark pytree_token as ephemeral in light/linear profiles (PyAutoGalaxy#374)
• xp-gate jax.scipy.special.factorial in shapelets/exponential.py (PyAutoGalaxy#385)

---

Full changelog: 2026.4.13.6...2026.5.1.4

v2026.4.13.6

PyAutoLens v2026.4.13.6

What's New

Bug Fixes

• fix: pin autogalaxy dependency version and update homepage URL (#435)

Upstream Changes

PyAutoFit

• fix: pin autoconf dependency version and update homepage URL (#1206)

PyAutoArray

• fix: pin autoconf dependency version and update homepage URL (#273)

PyAutoGalaxy

• fix: pin autofit/autoarray dependency versions and update homepage (#348)

---

Full changelog: 2026.4.13.5...2026.4.13.6

v2026.4.13.5

PyAutoLens v2026.4.13.5

What's New

Bug Fixes

• fix: pin autogalaxy dependency version and update homepage URL (#435)

Upstream Changes

PyAutoFit

• fix: pin autoconf dependency version and update homepage URL (#1206)

PyAutoArray

• fix: pin autoconf dependency version and update homepage URL (#273)

PyAutoGalaxy

• fix: pin autofit/autoarray dependency versions and update homepage (#348)

---

Full changelog: 2026.4.13.3...2026.4.13.5