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test: migrate stats/base/dists/kumaraswamy/stdev to ULP-based assertions #15533

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Merged
kgryte merged 1 commit into from
Sep 25, 2026
Merged

test: migrate stats/base/dists/kumaraswamy/stdev to ULP-based assertions #15533

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27 changes: 9 additions & 18 deletions lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/test/test.js
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Original file line number Diff line number Diff line change
Expand Up @@ -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 PINF = require( '@stdlib/constants/float64/pinf' );
var NINF = require( '@stdlib/constants/float64/ninf' );
var EPS = require( '@stdlib/constants/float64/eps' );
var abs = require( '@stdlib/math/base/special/abs' );
var stdev = require( './../lib' );


Expand Down Expand Up @@ -105,8 +104,6 @@ tape( 'if provided a nonpositive `b`, the function returns `NaN`', function test

tape( 'the function returns the standard deviation of a Kumaraswamy\'s double bounded distribution', function test( t ) {
var expected;
var delta;
var tol;
var a;
var b;
var i;
Expand All @@ -115,22 +112,16 @@ tape( 'the function returns the standard deviation of a Kumaraswamy\'s double bo
expected = data.expected;
a = data.a;
b = data.b;

/*
* High tolerance needed due to compounding errors in σ = √(m₂ - m₁²):
* - Two beta function evaluations with different parameters
* - Subtraction precision loss when m₂ ≈ m₁²
* - Square root operation amplifying small errors
*/
for ( i = 0; i < expected.length; i++ ) {
y = stdev( a[i], b[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[ i ] );

/*
* High tolerance needed due to compounding errors in σ = √(m₂ - m₁²):
* - Two beta function evaluations with different parameters
* - Subtraction precision loss when m₂ ≈ m₁²
* - Square root operation amplifying small errors
*/
tol = 10000 * EPS * abs( expected[ i ] );
t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
}
t.strictEqual( isAlmostSameValue( y, expected[ i ], 10564 ), true, 'returns expected value' );
}
t.end();
});
27 changes: 9 additions & 18 deletions lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/stdev/test/test.native.js
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Original file line number Diff line number Diff line change
Expand Up @@ -23,11 +23,10 @@
var resolve = require( 'path' ).resolve;
var tape = require( 'tape' );
var tryRequire = require( '@stdlib/utils/try-require' );
var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var PINF = require( '@stdlib/constants/float64/pinf' );
var NINF = require( '@stdlib/constants/float64/ninf' );
var EPS = require( '@stdlib/constants/float64/eps' );
var abs = require( '@stdlib/math/base/special/abs' );


// FIXTURES //
Expand Down Expand Up @@ -117,8 +116,6 @@ tape( 'if provided a nonpositive `b`, the function returns `NaN`', opts, functio

tape( 'the function returns the standard deviation of a Kumaraswamy\'s double bounded distribution', opts, function test( t ) {
var expected;
var delta;
var tol;
var a;
var b;
var i;
Expand All @@ -127,22 +124,16 @@ tape( 'the function returns the standard deviation of a Kumaraswamy\'s double bo
expected = data.expected;
a = data.a;
b = data.b;

/*
* High tolerance needed due to compounding errors in σ = √(m₂ - m₁²):
* - Two beta function evaluations with different parameters
* - Subtraction precision loss when m₂ ≈ m₁²
* - Square root operation amplifying small errors
*/
for ( i = 0; i < expected.length; i++ ) {
y = stdev( a[i], b[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[ i ] );

/*
* High tolerance needed due to compounding errors in σ = √(m₂ - m₁²):
* - Two beta function evaluations with different parameters
* - Subtraction precision loss when m₂ ≈ m₁²
* - Square root operation amplifying small errors
*/
tol = 18500 * EPS * abs( expected[ i ] );
t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
}
t.strictEqual( isAlmostSameValue( y, expected[ i ], 10564 ), true, 'returns expected value' );
}
t.end();
});
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