test: migrate stats/base/dists/levy/logcdf to ULP-based assertions

[Planeshifter]

Resolves a part of #11352.

Description

What is the purpose of this pull request?

This pull request:

• migrates the stats/base/dists/levy/logcdf test suite (test.logcdf.js, test.factory.js, test.native.js) from the relative-tolerance (EPS/abs-based) idiom to @stdlib/assert/is-almost-same-value-based ULP difference assertions.
• determines the tightest ULP bound per test body by computing the exact ULP difference (via @stdlib/number/float64/base/ulp-difference) between the actual and expected fixture values, for both the JavaScript implementation and the built native (C) addon, and confirms the result is deterministic across repeated runs.
• final ULP constant used: ULP = 0 (exact match) for all three converted files (test.logcdf.js, test.factory.js, test.native.js), across all three fixture sets (positive_mean, negative_mean, large_variance).

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: Migrate math/base/special packages from relative tolerance testing to ULP difference testing (tracking issue) #11352

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.

Only the test files in stats/base/dists/levy/logcdf/test/ were changed; no package.json changes were needed. make test TESTS_FILTER=".*/stats/base/dists/levy/logcdf/.*" passes for all four test files (test.js: 3/3, test.logcdf.js: 3016/3016, test.factory.js: 3020/3020, test.native.js: 3016/3016, the latter run against a locally built native addon), run twice to confirm determinism, and npx eslint reports no lint errors on the changed files.

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

If you answered "yes" to using AI assistance, please provide a short disclosure indicating how you used AI assistance. This helps reviewers determine how much scrutiny to apply when reviewing your contribution. Example disclosures: "This PR was written primarily by Claude Code." or "I consulted ChatGPT to understand the codebase, but the proposed changes were fully authored manually by myself.".

This PR was written primarily by Claude Code, including computing the tightest ULP bounds and applying the test-file edits.

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@stdlib-js/reviewers

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🤖 Generated with Claude Code

https://claude.ai/code/session_01FNJXXvVVMrtVcU25HhpuJ7

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Generated by Claude Code

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/levy/logcdf	$\\color{green}311/311$ $\\color{green}+100.00\\%$	$\\color{green}23/23$ $\\color{green}+100.00\\%$	$\\color{green}4/4$ $\\color{green}+100.00\\%$	$\\color{green}311/311$ $\\color{green}+100.00\\%$

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