From 6c4449bd1abcd5c43ebe3cb92b0f5daac2e0ea1d Mon Sep 17 00:00:00 2001
From: kgryte <kgryte+claude@gmail.com>
Date: Tue, 11 Aug 2026 18:19:31 +0000
Subject: [PATCH] test: migrate `stats/base/dists/beta/median` to ULP-based
 assertions

Replaces the computed relative tolerance (`15.0 * EPS * abs( expected )`)
in the fixture loop with an ULP-based assertion using
`@stdlib/assert/is-almost-same-value`. The ULP bound was tightened to the
measured minimum over the full fixture set (15 ULP; 14 fails).

Ref: https://github.com/stdlib-js/stdlib/issues/11352

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WT1k4EJXMZQLG6FfPXP8kR
---
 .../stats/base/dists/beta/median/test/test.js       | 13 ++-----------
 1 file changed, 2 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/median/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/beta/median/test/test.js
index 7d1a3b496c00..c9312eaf683b 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/beta/median/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/beta/median/test/test.js
@@ -21,11 +21,10 @@
 // MODULES //
 
 var tape = require( 'tape' );
+var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var median = require( './../lib' );
 
 
@@ -96,10 +95,8 @@ tape( 'if provided `beta <= 0`, the function returns `NaN`', function test( t )
 
 tape( 'the function returns the median of a beta distribution', function test( t ) {
 	var expected;
-	var delta;
 	var alpha;
 	var beta;
-	var tol;
 	var i;
 	var y;
 
@@ -108,13 +105,7 @@ tape( 'the function returns the median of a beta distribution', function test( t
 	beta = data.beta;
 	for ( i = 0; i < expected.length; i++ ) {
 		y = median( alpha[i], beta[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 15.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[ i ], 15 ), true, 'returns expected value' );
 	}
 	t.end();
 });