Keep von Mises pdf stable after norm_const access

[FlorianPfaff]

Summary

• keep automatically computed von Mises normalizers from changing pdf() to the unstable unscaled evaluation path
• preserve explicit norm_const behavior for callers that provide one
• add a regression test for large-concentration PDF evaluation after norm_const has been accessed

Bug fixed

For large concentrations, norm_const can overflow because it uses the unscaled Bessel function iv(0, kappa). Accessing dist.norm_const therefore cached inf; later dist.pdf() switched to exp(kappa * cos(...)) / norm_const, which evaluates to inf / inf at the mode and returns nan. The default pdf() path is already stable via ive, so the fix keeps auto-computed normalizers on that scaled path.

Validation

• python -m py_compile src/pyrecest/distributions/circle/von_mises_distribution.py tests/distributions/test_von_mises_distribution.py on the patched files
• Reproduced the numerical failure locally with SciPy/NumPy formulas (kappa=1000, mode point): unscaled path produced nan, scaled path stayed finite
• Full repository test suite was not run because the execution sandbox cannot resolve github.com to clone/install the repository

[github-actions]

✅MegaLinter analysis: Success

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✅ PYTHON	isort	1044	69	0	0	5.55s
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✅ REPOSITORY	git_diff	yes		no	no	0.2s
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