From ab947f1d95cac4a45cf32b7c92cde6f10d2ebbef Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 12 Sep 2026 06:13:09 +0000 Subject: [PATCH] test: migrate `stats/base/dists/beta/kurtosis` to ULP-based assertions Migrate the computed relative tolerance assertions to ULP difference assertions using `@stdlib/assert/is-almost-same-value`. Both the JavaScript and C implementations reproduce the reference fixture values bit-for-bit, and thus the minimum required ULP bound is zero. Ref: https://github.com/stdlib-js/stdlib/issues/11352 Co-Authored-By: Claude Opus 5 Claude-Session: https://claude.ai/code/session_018pww2eTE6dBtB2G1jEpVDr --- .../stats/base/dists/beta/kurtosis/test/test.js | 13 ++----------- .../base/dists/beta/kurtosis/test/test.native.js | 13 ++----------- 2 files changed, 4 insertions(+), 22 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.js index 9a5e0a60ffc6..34968b7cacea 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/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 kurtosis = require( './../lib' ); @@ -96,10 +95,8 @@ tape( 'if provided `beta <= 0`, the function returns `NaN`', function test( t ) tape( 'the function returns the excess kurtosis 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 excess kurtosis of a beta distribution', functio beta = data.beta; for ( i = 0; i < expected.length; i++ ) { y = kurtosis( 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 = 1.0 * 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 ], 0 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.native.js index 1c91fce582d8..926acf3e372d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/test/test.native.js @@ -22,12 +22,11 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); -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' ); // FIXTURES // @@ -105,10 +104,8 @@ tape( 'if provided `beta <= 0`, the function returns `NaN`', opts, function test tape( 'the function returns the excess kurtosis of a beta distribution', opts, function test( t ) { var expected; - var delta; var alpha; var beta; - var tol; var i; var y; @@ -117,13 +114,7 @@ tape( 'the function returns the excess kurtosis of a beta distribution', opts, f beta = data.beta; for ( i = 0; i < expected.length; i++ ) { y = kurtosis( 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 = 2.0 * 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 ], 0 ), true, 'returns expected value' ); } t.end(); });