From 508cdea0beef8247f082c1121ac68e6a28d3d7eb Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 9 Oct 2026 02:23:34 +0000
Subject: [PATCH] test: migrate `stats/base/dists/logistic/median` to ULP-based
 assertions

Replace relative tolerance assertions with ULP difference assertions
using `@stdlib/assert/is-almost-same-value`. All one hundred fixture
values match bitwise, so the minimum required ULP bound is `0`.

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_012Nh3iDy9gFehtejnTZ9Gg1
---
 .../stats/base/dists/logistic/median/test/test.js   | 13 ++-----------
 1 file changed, 2 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/median/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/median/test/test.js
index 0442e2d3ce83..5066b9725f6a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/median/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/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' );
 
 
@@ -76,8 +75,6 @@ tape( 'if provided a nonpositive `s`, the function returns `NaN`', function test
 
 tape( 'the function returns the median of a logistic distribution', function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var mu;
 	var s;
 	var y;
@@ -89,13 +86,7 @@ tape( 'the function returns the median of a logistic distribution', function tes
 	for ( i = 0; i < mu.length; i++ ) {
 		y = median( mu[i], s[i] );
 		if ( expected[i] !== null ) {
-			if ( y === expected[i] ) {
-				t.strictEqual( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
-			} else {
-				delta = abs( y - expected[ i ] );
-				tol = 1.0 * EPS * abs( expected[ i ] );
-				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
+			t.strictEqual( isAlmostSameValue( y, expected[ i ], 0 ), true, 'returns expected value' );
 		}
 	}
 	t.end();