test: migrate stats/base/dists/kumaraswamy/mode to ULP-based assertions

[kgryte]

Resolves a part of #11352.

Description

What is the purpose of this pull request?

This pull request:

• migrates the tests for stats/base/dists/kumaraswamy/mode from relative tolerance assertions to ULP-based assertions using @stdlib/assert/is-almost-same-value.
• updates both test/test.js and test/test.native.js, replacing the delta/tol comparison against 15.0 * EPS * abs( expected[ i ] ) with t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' );.
• removes the now unused @stdlib/math/base/special/abs and @stdlib/constants/float64/eps requires.

The final ULP constant is 1 in both test/test.js and test/test.native.js.

This is the measured minimum. Over the full Julia fixture set (100 cases), the largest observed ULP difference between the returned and expected values is exactly 1 (worst case: a = 4.650703332395438, b = 3.5899547415339503, returned 0.7308091452905936, expected 0.7308091452905935). Lowering the bound to 0 fails 14 of the fixture cases in each test file, so 1 is the tightest bound which passes.

Both test files were run twice at the final bound to confirm determinism (the native tests were exercised locally after building the add-on): test/test.js 120/120 passing and test/test.native.js 121/121 passing on both runs. Only the two test files are modified.

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.

No.

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)
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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 by Claude Code, running unattended, which selected the package, mirrored the idiom used in previously merged migrations, measured the minimum ULP bound against the fixture set, and verified the tests and lint locally.

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@stdlib-js/reviewers

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Generated by Claude Code

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/kumaraswamy/mode	$\\color{green}205/205$ $\\color{green}+100.00\\%$	$\\color{green}12/12$ $\\color{green}+100.00\\%$	$\\color{green}2/2$ $\\color{green}+100.00\\%$	$\\color{green}205/205$ $\\color{green}+100.00\\%$

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