Affected Repositories

• PyAutoArray (primary, and only)

Dropped from the prompt header after investigation: autolens_workspace and
autogalaxy_workspace need no change once the library is fixed; HowToGalaxy and
HowToLens do not carry the script.

Branch Survey

No worktree claims this task.

Suggested branch: feature/convolver-gaussian-small-datasets-cap

Root cause

autoarray/operators/convolver.py:721:

grid = Grid2D.uniform(shape_native=shape_native, pixel_scales=pixel_scales)

Grid2D.uniform shrinks grids >16x16 to (16, 16) at pixel_scales=0.6 when
PYAUTO_SMALL_DATASETS=1 (autoarray/structures/grids/uniform_2d.py:499). Line 746
then calls Array2D.no_mask(values=gaussian, shape_native=shape_native) with the
original (31, 31), so 256 values meet a 961-pixel mask:

ArrayException: array_2d_slim.shape = 256  vs  mask_2d.pixels_in_mask = 961, shape_native (31, 31)

Reproduced from autolens_workspace root:

PYAUTO_SMALL_DATASETS=1 PYAUTO_TEST_MODE=2 PYAUTO_SKIP_VISUALIZATION=1 \
PYAUTO_DISABLE_JAX=1 PYAUTO_FAST_PLOTS=1 \
python scripts/imaging/data_preparation/manual/mask_irregular.py

Fix verified by monkeypatching Grid2D.uniform in a scratch reproduction:
data (16,16) / kernel (31,31) / blurred (16,16) / mask (16,16), 111 pixels — clean.

Implementation Steps

1. autoarray/operators/convolver.py (~L721) — in Convolver.from_gaussian:

   grid = Grid2D.uniform(
       shape_native=shape_native,
       pixel_scales=pixel_scales,
       respect_small_datasets=False,  # kernel shape is intrinsic to the operator, not dataset size
   )
   

   Note this in the shape_native docstring entry: the kernel is built at the full
   requested size even under PYAUTO_SMALL_DATASETS=1.

2. test_autoarray/operators/test_convolver.py — numpy-only regression test using
   monkeypatch.setenv("PYAUTO_SMALL_DATASETS", "1"):

   • Convolver.from_gaussian(shape_native=(31, 31), pixel_scales=0.1, sigma=0.1)
     constructs without raising, kernel.shape_native == (31, 31);
   • it blurs a 16x16 Array2D to a 16x16 result (the mask_irregular geometry).
     Mirror the style of the neighbouring from_gaussian tests.

Verification

1. New test fails on main, passes after the fix.
2. Full PyAutoArray unit suite (shared Grid2D.uniform path).
3. mask_irregular.py runs clean under the smoke env in both workspaces.
4. Same scripts with PYAUTO_SMALL_DATASETS unset still pass (full-res path untouched).
5. Spot-check an 11x11 consumer (autolens_workspace/scripts/imaging/simulator.py) —
   below the cap, no behaviour change.

Blast radius

Any Convolver.from_gaussian(shape_native > 16x16) is currently broken in smoke mode.
A sweep of both workspaces + HowToLens/HowToGalaxy found four such call sites: the two
mask_irregular.py scripts (live, failing) and two (21, 21) sites
(autolens_workspace/scripts/imaging/simulator.py:435, guides/advanced/over_sampling.py:494)
that are latent — both in non-executed fenced prose blocks, and guides/ already unsets
the flag.

Rejected alternatives

• unset: [PYAUTO_SMALL_DATASETS] in each workspace config/build/env_vars.yaml (the
  prompt's suggestion) — papers over the library bug and leaves every >16x16 kernel broken.
• Capping the mask in the script — the mask is data-derived and already consistent once
  the kernel is right.
• Promoting these scripts to smoke_tests.txt — the smoke list stays a curated subset.

Key Files

• autoarray/operators/convolver.py — Convolver.from_gaussian, the one-line fix
• autoarray/structures/grids/uniform_2d.py:471-517 — Grid2D.uniform and the
  respect_small_datasets opt-out being reused
• autoarray/util/dataset_util.py — the SMALL_DATASETS cap constants for context
• test_autoarray/operators/test_convolver.py — new regression test

mask_irregular fails under SMALL_DATASETS: slim array 256 (16^2) vs mask 961 (31^2)

Type: bug
Target: autoarray
Repos:

• autogalaxy_workspace
• autolens_workspace
• HowToGalaxy
• HowToLens
• PyAutoArray
  Difficulty: small
  Autonomy: supervised
  Priority: normal
  Status: formalised

Un-parked by a parallel chat (old "silent failure" resolved) — now the REAL error is a
SMALL_DATASETS cap mismatch, i.e. an env-config gap, not a deep code bug:

imaging/data_preparation/manual/mask_irregular.py
  autoarray/structures/arrays/array_2d_util.py:69 check_array_2d_and_mask_2d
  ArrayException: slim array_2d_slim.shape = 256  vs  mask_2d.pixels_in_mask = 961, shape_native (31,31)

The data array is capped to 16x16 (256) under PYAUTO_SMALL_DATASETS=1 but the manually-drawn
irregular mask is 31x31 (961) — sizes disagree. Fix options (mirror the 2026-07-21 cap/should_simulate
work): add a per-script unset: [PYAUTO_SMALL_DATASETS] override in each repo's config/build/env_vars.yaml
(this script loads pre-committed/real data at full res), OR cap the mask via the same 16x16 lever.
Affected: autogalaxy_workspace + autolens_workspace (+ HowToGalaxy/HowToLens if they carry the script).
Currently un-parked and FAILING — remove/refresh any NEEDS_FIX marker once green.