feat: add implementation for stats/base/dists/halfnormal/quantile

[Om-A-osc]

Progressess #9416.

Description

What is the purpose of this pull request?

This pull request adds a complete implementation of the Half-Normal distribution quantile function (halfnormal/quantile) across the JavaScript, native C, and N-API layers.

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: Tracking issue for complete implementation of @stdlib/stats/base/dists/halfnormal package #9416

Questions

Any questions for reviewers of this pull request?

No.

Other

Any other information relevant to this pull request? This may include screenshots, references, and/or implementation notes.

All tests, benchmarks, and examples pass for both JavaScript and C implementations. The implementation handles edge cases correctly, including invalid probabilities, non-positive scale parameters, the degenerate case σ = 0, and p = 1 returning +Infinity.

Checklist

Please ensure the following tasks are completed before submitting this pull request.

• Read, understood, and followed the contributing guidelines.

AI Assistance

When authoring the changes proposed in this PR, did you use any kind of AI assistance?

• Yes
• No

If you answered "yes" above, how did you use AI assistance?

• Code generation (e.g., when writing an implementation or fixing a bug)
• Test/benchmark generation
• Documentation (including examples)
• Research and understanding

Disclosure

I used ChatGPT to help derive and verify the half-normal quantile formula.

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@stdlib-js/reviewers

[Planeshifter]

Looks close to be ready.

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/halfnormal/quantile	$\color{green}306/306$ $\color{green}+0.00%$	$\color{green}29/29$ $\color{green}+0.00%$	$\color{green}4/4$ $\color{green}+0.00%$	$\color{green}306/306$ $\color{green}+0.00%$

The above coverage report was generated for the changes in this PR.

[Om-A-osc]

Thank you @Planeshifter for reviewing my PR. I’ve addressed the style issue in main.c and ensured that Half-normal is used consistently as the name throughout the package. Please let me know if anything else needs to be updated.

[Neerajpathak07]

@Om-A-osc This PR will need a bit off refactoring. I suggest you to take a closer look at how the statistical distribution packages are implemented w.r.t the current code convention.
A few examples that I have in mind are:-

• wald/pdf
• wald/mean
• halfnormal/stdev

[Om-A-osc]

@Neerajpathak07 @Planeshifter
I’ve addressed all the review comments in this PR.

Summary of changes:

• Switched to @stdlib/random/array/uniform where appropriate.
• Migrated fixture generation from Julia to SciPy, as Julia does not provide a Half-Normal distribution API suitable for generating quantile fixtures.
• Fixed fixture loading and usage in the test files to ensure consistency across JS and native implementations.
• Updated benchmark files to use format for consistency and correctness.
• Made a few other minor cleanup and consistency changes.

All tests, linters, and benchmarks (JS + native) are now passing .

Thank you for taking the time to review this and for the helpful feedback. Please have a look when you get a chance I’m happy to make any further adjustments if needed.

[Om-A-osc]

@kgryte Thank you for your review. I did couple of requested changes. Have a look whenever free.

[Om-A-osc]

@Planeshifter Completed the requested changes for halfnormal/quantile.

[Om-A-osc]

@Planeshifter Thank you for your review. I have made the requested changes.