Reject non-finite UKF vectors and keep failed predictions atomic

[FlorianPfaff]

Summary

• reject non-finite UKF transition outputs, measurements, and measurement-model outputs at the vector boundary
• build predicted sigma points before committing x/P, so covariance-validation failures do not corrupt filter state
• add regressions covering NaN/Inf inputs and failed predicted-covariance validation

Bug

The internal UKF previously allowed NaN/Inf vectors through _as_vector. In addition, predict() assigned self.x and self.P before regenerating/validating sigma points from the predicted covariance. If that validation failed (for example because Q made the predicted covariance non-finite), the method raised after leaving the filter in a partially updated invalid state.

Tests

Added tests/filters/test_ukf_nonfinite_atomicity.py with regressions for:

• non-finite transition output
• non-finite measurement
• non-finite measurement-model output
• atomic failure when the predicted covariance is non-finite

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Max errors	Warnings	Elapsed time
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✅ JSON	prettier	7	0	0		0	0.81s
✅ JSON	v8r	7		0		0	4.17s
✅ MARKDOWN	markdownlint	68	0	0		0	2.1s
✅ MARKDOWN	markdown-table-formatter	68	0	0		0	0.45s
✅ PYTHON	black	2024	6	0		0	59.79s
✅ PYTHON	isort	2024	9	0		0	2.85s
✅ REPOSITORY	betterleaks	yes		no		no	1.38s
✅ REPOSITORY	checkov	yes		no		no	34.95s
✅ REPOSITORY	git_diff	yes		no		no	0.16s
✅ REPOSITORY	secretlint	yes		no		no	105.53s
✅ REPOSITORY	syft	yes		no		no	3.42s
✅ REPOSITORY	trivy-sbom	yes		no		no	2.93s
✅ YAML	prettier	11	0	0		0	0.61s
✅ YAML	v8r	11		0		0	16.95s
✅ YAML	yamllint	11		0		0	1.08s

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