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test: migrate math/base/special/ln to ULP difference testing #13742

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Merged
kgryte merged 1 commit into from
Jul 29, 2026
Merged

test: migrate math/base/special/ln to ULP difference testing #13742

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104 changes: 29 additions & 75 deletions lib/node_modules/@stdlib/math/base/special/ln/test/test.js
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Original file line number Diff line number Diff line change
Expand Up @@ -24,10 +24,10 @@ var tape = require( 'tape' );
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 pow = require( '@stdlib/math/base/special/pow' );
var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
var ln = require( './../lib' );


Expand All @@ -52,161 +52,119 @@ tape( 'main export is a function', function test( t ) {

tape( 'the function evaluates the natural logarithm of `x` (very large positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = veryLargePositive.expected;
x = veryLargePositive.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (large positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = largePositive.expected;
x = largePositive.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (medium positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = mediumPositive.expected;
x = mediumPositive.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (small positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = smallPositive.expected;
x = smallPositive.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (smaller positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = smaller.expected;
x = smaller.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (tiny positive values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = tinyPositive.expected;
x = tinyPositive.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});

tape( 'the function evaluates the natural logarithm of `x` (subnormal values)', function test( t ) {
var expected;
var delta;
var tol;
var x;
var y;
var i;
var e;

expected = subnormal.expected;
x = subnormal.x;
for ( i = 0; i < x.length; i++ ) {
y = ln( x[i] );
if ( y === expected[i] ) {
t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] );
} else {
delta = abs( y - expected[i] );
tol = EPS * abs( expected[i] );
t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. Tolerance: '+tol+'.' );
}
e = expected[ i ];
t.strictEqual( isAlmostSameValue( y, e, 1 ), true, 'returns expected value' );
}
t.end();
});
Expand Down Expand Up @@ -235,27 +193,23 @@ tape( 'the function returns positive zero if provided `1.0`', function test( t )
});

tape( 'the function evaluates the natural logarithm for powers of 2', function test( t ) {
var delta;
var tol;
var v;
var e;

// Test ln(2) - should trigger k !== 0 and f === 0.0 path
v = ln( 2.0 );
delta = abs( v - 0.6931471805599453 );
tol = EPS * abs( 0.6931471805599453 );
t.strictEqual( delta <= tol, true, 'returns expected value' );
e = 0.6931471805599453;
t.strictEqual( isAlmostSameValue( v, e, 1 ), true, 'returns expected value' );

// Test ln(4) - should trigger k !== 0 and f === 0.0 path
v = ln( 4.0 );
delta = abs( v - 1.3862943611198906 );
tol = EPS * abs( 1.3862943611198906 );
t.strictEqual( delta <= tol, true, 'returns expected value' );
e = 1.3862943611198906;
t.strictEqual( isAlmostSameValue( v, e, 1 ), true, 'returns expected value' );

// Test ln(0.5) - should trigger k !== 0 and f === 0.0 path
v = ln( 0.5 );
delta = abs( v - (-0.6931471805599453) );
tol = EPS * abs( -0.6931471805599453 );
t.strictEqual( delta <= tol, true, 'returns expected value' );
e = -0.6931471805599453;
t.strictEqual( isAlmostSameValue( v, e, 1 ), true, 'returns expected value' );

t.end();
});
Expand Down
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