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chore: clean-up #15426

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Merged
kgryte merged 2 commits into from
Sep 23, 2026
Merged

chore: clean-up #15426

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0d3105d
refactor: align JS and C operation order in `stats/base/dists/*`
claude Sep 22, 2026
44facd7
test: tighten ULP bound in `stats/base/dists/hypergeometric/mean`
claude Sep 22, 2026
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4 changes: 2 additions & 2 deletions lib/node_modules/@stdlib/stats/base/dists/chi/skewness/lib/main.js
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Original file line number Diff line number Diff line change
Expand Up @@ -59,8 +59,8 @@ function skewness( k ) {
return NaN;
}
mu = mean( k );
sigma = sqrt( variance( k ) );
sigma2 = sigma * sigma;
sigma2 = variance( k );
sigma = sqrt( sigma2 );
sigma3 = sigma2 * sigma;
return ( mu / sigma3 ) * ( 1.0 - ( 2.0*sigma2 ) );
}
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2 changes: 1 addition & 1 deletion lib/node_modules/@stdlib/stats/base/dists/hypergeometric/mean/lib/main.js
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Expand Up @@ -82,7 +82,7 @@ function mean( N, K, n ) {
) {
return NaN;
}
return n * ( K / N );
return ( n * K ) / N;

@kgryte kgryte Sep 23, 2026

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In principle, this computation has a greater risk of overflow, including just to the realm beyond safe integers. However, practically speaking, that is not a common use case, so I am fine having this match the C implementation.

@Planeshifter Planeshifter Sep 23, 2026

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Confirmed, and worth pinning down the boundary: the product overflows once n*K exceeds sqrt(MAX_VALUE) ≈ 1.34e154, so mean( 1e160, 1e160, 1e160 ) now returns Infinity where the previous arrangement returned 1e160.

The asymmetry is JS-only. src/main.c takes int32_t, so the C cannot reach that regime at all, whereas the JS guard is isNonNegativeInteger, which accepts 1e300. So this is a case where matching the C narrows the JS domain rather than just reordering within it.

Leaving as-is per your call. Noting the threshold here so it's on the record if anyone later hits it.

Generated by Claude Code

}


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2 changes: 1 addition & 1 deletion lib/node_modules/@stdlib/stats/base/dists/hypergeometric/mean/test/test.js
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Expand Up @@ -130,7 +130,7 @@ tape( 'the function returns the mean of a hypergeometric distribution', function
n = data.n;
for ( i = 0; i < n.length; i++ ) {
y = mean( N[i], K[i], n[i] );
t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' );
t.strictEqual( isAlmostSameValue( y, expected[ i ], 0 ), true, 'returns expected value' );
}
t.end();
});
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