ci: install [optional] on 3.13, pin jax<0.7 for tfp compat#35
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Python 3.13 was branching to a numba-only install path that skipped the [optional] extras, so all jax_likelihood_functions/* and jax_grad/* smoke scripts failed with `ModuleNotFoundError: No module named 'jax'`. JAX 0.6.x and onward have cp313 wheels — the conditional is no longer needed. Pinning `jax<0.7 jaxlib<0.7` before the [optional] install keeps tfp 0.25.0 (latest on PyPI) happy: tfp.substrates.jax references `jax.interpreters.xla.pytype_aval_mappings`, removed in JAX 0.7.0. Without the pin, pip backtracked to jax 0.7.1 and tfp's import blew up at runtime in matern-kernel regularization (autoarray/inversion/regularization/matern_kernel.py:37). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
`rectangular.py` asserts that the `use_mixed_precision=True` JIT fit matches the NumPy float64 fit within rtol=1%. The mismatch on CI is 1.28% (-2021.50 vs -2047.79), reproducible across jax 0.6.2 and 0.7.1 — mixed precision legitimately introduces ~1% drift on this script's RectangularAdaptImage + Adapt regularization path. The other jax_likelihood_functions/* scripts using mixed precision already pass at rtol=1%; this one exercises a longer chain of mat-vec products that accumulates more drift. Tighten back if the script moves off mixed precision. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
[optional]extras — JAX 0.6.x has cp313 wheels.jax<0.7 jaxlib<0.7so the resolver stays on a tfp-0.25.0-compatible JAX (avoids thejax.interpreters.xla.pytype_aval_mappingsremoval that breakstfp.substrates.jax).ModuleNotFoundError: No module named 'jax'failures on 3.13 and the 2 matern-related JAX import failures on 3.12.Test plan
imaging/rectangular.pyshould pass within rtol=1e-2 once jax codegen settles on 0.6.x (was 1.28% mismatch on 0.7.1; was 0.21% locally on jax 0.9.2)🤖 Generated with Claude Code