Normalize wrapped Laplace scalar parameters

[FlorianPfaff]

Summary

• normalize accepted one-element wrapped-Laplace parameter arrays to zero-dimensional backend scalars
• preserve Python, NumPy, and backend scalar parameter behavior
• add regression coverage for parameter, PDF, and trigonometric-moment output shapes

Bug

WrappedLaplaceDistribution documents lambda_ and kappa_ as scalars, but _validate_positive_scalar() accepted arrays with shape (1,) and returned them unchanged.

This made scalar behavior depend on how numerically identical parameters were supplied. With lambda_=2.0 and kappa_=1.3, scalar pdf() and trigonometric_moment() calls return scalar values. With one-element arrays such as np.array([2.0]), the retained singleton axes broadcast through the formulas and produce arrays with shape (1,) instead.

That accidental batch axis can break scalar consumers and makes the wrapped-Laplace API inconsistent with its scalar parameter contract.

Fix

After validating that a parameter is either zero-dimensional or a one-element array, reshape the latter to a zero-dimensional backend value. Numerical values and valid scalar behavior are unchanged.

Validation

• regression verifies that stored lambda_ and kappa values have shape ()
• regression verifies scalar pdf() and first trigonometric-moment outputs also have shape ()
• modified source and regression modules pass python -m py_compile
• deterministic NumPy smoke confirms (1,) parameters normalize to ()
• branch comparison against current main: two commits ahead, zero behind; two production lines and one focused regression file changed

The full backend and lint matrix is delegated to GitHub Actions.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	20.06s
✅ JSON	prettier	7	0	0	0	1.27s
✅ JSON	v8r	7		0	0	4.03s
✅ MARKDOWN	markdownlint	68	0	0	0	1.91s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	0.93s
✅ PYTHON	black	1490	182	0	0	86.07s
✅ PYTHON	isort	1490	328	0	0	2.46s
✅ REPOSITORY	betterleaks	yes		no	no	2.28s
✅ REPOSITORY	checkov	yes		no	no	49.44s
✅ REPOSITORY	gitleaks	yes		no	no	13.94s
✅ REPOSITORY	git_diff	yes		no	no	0.3s
✅ REPOSITORY	secretlint	yes		no	no	60.43s
✅ REPOSITORY	syft	yes		no	no	5.83s
✅ REPOSITORY	trivy-sbom	yes		no	no	5.62s
✅ REPOSITORY	trufflehog	yes		no	no	30.15s
✅ YAML	prettier	11	0	0	0	0.75s
✅ YAML	v8r	11		0	0	10.17s
✅ YAML	yamllint	11		0	0	0.55s

Notices

📣 MegaLinter 9.5.0 is out! Discover the new features and security recommendations in the release announcement. (Skip this info by defining SECURITY_SUGGESTIONS: false)

See detailed reports in MegaLinter artifacts

Your project could benefit from a custom flavor, which would allow you to run only the linters you need, and thus improve runtime performances. (Skip this info by defining FLAVOR_SUGGESTIONS: false)

• Documentation: Custom Flavors
• Command: npx mega-linter-runner@9.6.0 --custom-flavor-setup --custom-flavor-linters PYTHON_BLACK,PYTHON_ISORT,COPYPASTE_JSCPD,JSON_V8R,JSON_PRETTIER,MARKDOWN_MARKDOWNLINT,MARKDOWN_MARKDOWN_TABLE_FORMATTER,REPOSITORY_CHECKOV,REPOSITORY_GIT_DIFF,REPOSITORY_GITLEAKS,REPOSITORY_BETTERLEAKS,REPOSITORY_SECRETLINT,REPOSITORY_SYFT,REPOSITORY_TRIVY_SBOM,REPOSITORY_TRUFFLEHOG,YAML_PRETTIER,YAML_YAMLLINT,YAML_V8R

Show us your support by starring ⭐ the repository