docs: tutorial 8 — numba remains the CPU route for pixelized sources (#506) - #75
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…(#506) Chapter 2 tutorial 8 said JAX supersedes `numba` outright. True for the light-profile likelihood, but not for pixelized-source modeling on a CPU, where the `numba` sparse-operator path is still faster on many-core machines. One sentence appended noting the exception and pointing at `autolens_workspace/scripts/imaging/features/pixelization/cpu_fast_modeling.py` and chapter 3. Prose only; no code or behaviour change. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01XySQZP6Npj4adZMkYZ96Bo
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01XySQZP6Npj4adZMkYZ96Bo
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Summary
Chapter 2, tutorial 8 (
the need for speed) tells the reader that JAX supersedesnumbaoutright.That is true for the light-profile likelihood, but not for pixelized-source modeling on a CPU, where
the
numbasparse-operator path is still the faster route on many-core machines — leaving thetutorial's claim unqualified sends CPU users down the slower path.
One sentence is appended in the same voice, pointing at
autolens_workspace/scripts/imaging/features/pixelization/cpu_fast_modeling.pyand chapter 3.Prose only — no code or behaviour change.
Scripts Changed
scripts/chapter_2_lens_modeling/tutorial_8_need_for_speed.py— one sentence appended to theJAX-supersedes-
numbaparagraph noting the pixelized-source CPU exception.Test Plan
python -c "import ast; ast.parse(open(...).read())"on the edited script — parses.Part of PyAutoLabs/autolens_workspace#506.
Generated by the PyAutoLabs agent workflow.