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smoke profile: PYAUTO_FAST_PLOTS=1, as the autolens/autogalaxy profiles set - #31
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…es set imaging_ci/modeling/start_here.py is the slowest smoke script on the Heart board (89.5s py3.13 / 61.0s py3.12, 68% of its leg, run 33792233410). Profiled locally under this profile with the libraries from source: the bypassed fit itself is cheap; the time is (a) a per-pixel Python loop in PyAutoArray's over-sampled grid builder, run for a border relocator the CTI fit never uses (~50s of 117s local — fixed in PyAutoArray on the same branch name), and (b) the ~100 on-the-fly figures per run: ~17s of matplotlib rasterisation + PNG writes and ~20-40s of mask-edge overlay derivation on the 2000x100 frame. This flag drops each figure before it is drawn or saved (every plot call still runs — the extraction, zoom and subplot layout are exercised), and with the PyAutoArray branch it also skips the overlay derivation. Measured cold (dataset simulated inside the run), same machine: baseline 117.3s PyAutoArray fix only 58.5s PyAutoArray fix + this profile 25.9s (warm, dataset present: 15.9s) Found and measured by PyAutoBrain `hygiene ci` + /ci_speedup. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015J8ZLmc55ZT1nSRntZMz9K
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Summary
imaging_ci/modeling/start_here.pyis the slowest smoke script on the Heart board (89.5s py3.13 / 61.0s py3.12, 68% of its leg, run 33792233410). Profiled locally under this profile with the libraries from source: the bypassed fit itself is cheap; the time is (a) a per-pixel Python loop in PyAutoArray's over-sampled grid builder, run for a border relocator the CTI fit never uses (~50s of 117s local — fixed in PyAutoLabs/PyAutoArray#534), and (b) the ~100 on-the-fly figures per run: ~17s of matplotlib rasterisation + PNG writes and ~20–40s of mask-edge overlay derivation on the 2000x100 frame.This flag drops each figure before it is drawn or saved, exactly as the autolens / autogalaxy smoke profiles already do (every plot call still runs — the extraction, zoom and subplot layout are exercised). It is independent of the library PR:
PYAUTO_FAST_PLOTSis an existing flag, so this merges safely on its own; the mask-edge skip lands with PyAutoArray#534. Measured cold (dataset simulated inside the run), same machine:Found and measured by PyAutoBrain
hygiene ci+/ci_speedup.Scripts Changed
config/build/profile_smoke.yaml—defaultsgainsPYAUTO_FAST_PLOTS: "1"with the measured rationale (validated withvalidate_env_profiles.py --strict-declarations: 0 errors, 0 warnings). No script edited.Test Plan
imaging_ci/modeling/start_here.pypasses locally under the new profile, cold and warmGenerated by the PyAutoLabs agent workflow.
🤖 Generated with Claude Code
https://claude.ai/code/session_015J8ZLmc55ZT1nSRntZMz9K
Generated by Claude Code