Validate bias application feature rows

[FlorianPfaff]

Summary

• Add an explicit SensorBiasCorrectionModel.apply shape check after bias prediction.
• Reject feature arrays that do not produce exactly one predicted bias row per measurement.
• Add regression coverage for mismatched and matching feature row counts.

Bug fixed

For nonconstant bias models, predict(features, n_rows=...) returns one bias row per feature row. apply() previously proceeded without checking that the predicted bias matrix matched the measurement matrix, so a single feature row could be silently broadcast to multiple measurements, or other row mismatches could fail later via NumPy boolean indexing/broadcasting. The patch fails fast with a clear ValueError.

Validation

• Branch created from current main (acd35ff2fc999a78ae13d2116af1fba85aa0c39e).
• Compared branch against main: 2 commits ahead, 0 behind; only src/pyrecest/calibration/bias.py and a focused calibration regression test changed.
• Local pytest was not run because this execution environment cannot clone/install the repository from GitHub; repository CI should run the focused regression tests and full suite.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	44.73s
✅ JSON	prettier	7	0	0	0	0.91s
✅ JSON	v8r	7		0	0	4.01s
✅ MARKDOWN	markdownlint	66	0	0	0	1.72s
✅ MARKDOWN	markdown-table-formatter	66	0	0	0	0.79s
✅ PYTHON	black	769	1	0	0	33.77s
✅ PYTHON	isort	769	2	0	0	2.21s
✅ REPOSITORY	checkov	yes		no	no	40.98s
✅ REPOSITORY	gitleaks	yes		no	no	15.48s
✅ REPOSITORY	git_diff	yes		no	no	0.06s
✅ REPOSITORY	secretlint	yes		no	no	25.13s
✅ REPOSITORY	syft	yes		no	no	3.65s
✅ REPOSITORY	trivy-sbom	yes		no	no	3.88s
✅ REPOSITORY	trufflehog	yes		no	no	21.14s
✅ YAML	prettier	11	0	0	0	0.68s
✅ YAML	v8r	11		0	0	10.92s
✅ YAML	yamllint	11		0	0	0.48s

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