Stabilize discrete-state prior normalization

[FlorianPfaff]

Summary

• normalize discrete-state probability vectors after max-scaling instead of summing raw weights
• prevent overflow for valid large finite HMM/IMM priors while preserving their ratios
• add regressions covering both discrete_forward_backward and imm_forward_backward

Bug

A valid prior such as [float_max, float_max / 2] previously overflowed when summed. The resulting inf denominator collapsed the normalized vector to zeros, causing filtering to fail with a spurious no-mass error.

Fix

Scale finite non-negative weights by their maximum before summing and normalizing. This also improves robustness for extremely small finite weights.

[github-actions]

✅MegaLinter analysis: Success

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✅ MARKDOWN	markdownlint	68	0	0		0	2.04s
✅ MARKDOWN	markdown-table-formatter	68	0	0		0	0.41s
✅ PYTHON	black	2023	6	0		0	66.23s
✅ PYTHON	isort	2023	8	0		0	3.0s
✅ REPOSITORY	betterleaks	yes		no		no	1.23s
✅ REPOSITORY	checkov	yes		no		no	35.08s
✅ REPOSITORY	git_diff	yes		no		no	0.14s
✅ REPOSITORY	secretlint	yes		no		no	106.04s
✅ REPOSITORY	syft	yes		no		no	3.38s
✅ REPOSITORY	trivy-sbom	yes		no		no	2.82s
✅ YAML	prettier	11	0	0		0	0.72s
✅ YAML	v8r	11		0		0	17.9s
✅ YAML	yamllint	11		0		0	1.06s

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