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bench: refactor random number generation in stats/base/dists/triangular #5211

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bench: refactor random number generation in stats/base/dists/triangular #5211

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ae5c2bb
bench(stats/base/dists/triangular): refactor random number generation…
G4URAV001 Feb 13, 2025
2d221a0
fixup! Made the suggested changes
G4URAV001 Feb 20, 2025
dee8eca
fixup! made the suggested change
G4URAV001 Feb 21, 2025
3fca2d5
Merge branch 'develop' into G4URAV001/issue4989
G4URAV001 Apr 2, 2025
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31 changes: 23 additions & 8 deletions lib/node_modules/@stdlib/stats/base/dists/triangular/cdf/benchmark/benchmark.js
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,8 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
var uniform = require( '@stdlib/random/base/uniform' );
var Float64Array = require( '@stdlib/array/float64' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var EPS = require( '@stdlib/constants/float64/eps' );
var pkg = require( './../package.json' ).name;
Expand All @@ -34,17 +35,26 @@ bench( pkg, function benchmark( b ) {
var mode;
var min;
var max;
var len;
var x;
var y;
var i;

len = 100;
x = new Float64Array( len );
min = new Float64Array( len );
max = new Float64Array( len );
mode = new Float64Array( len );
for ( i = 0; i < len; i++ ) {
x[ i ] = uniform( 0.0, 30.0 );
min[ i ] = uniform( 0.0, 10.0 );
max[ i ] = uniform( min[ i ] + EPS, min[ i ] + 40.0 );
mode[ i ] = uniform( min[ i ], max[ i ] );
}

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
x = randu() * 30.0;
min = randu() * 10.0;
max = min + ( randu() * 40.0 ) + EPS;
mode = min + ( ( max - min ) * randu() );
y = cdf( x, min, max, mode );
y = cdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand All @@ -62,6 +72,7 @@ bench( pkg+':factory', function benchmark( b ) {
var mode;
var min;
var max;
var len;
var x;
var y;
var i;
Expand All @@ -70,11 +81,15 @@ bench( pkg+':factory', function benchmark( b ) {
max = 1.5;
mode = 0.5;
mycdf = cdf.factory( min, max, mode );
len = 100;
x = new Float64Array( len );
for ( i = 0; i < len; i++ ) {
x[ i ] = uniform( -2.0, 0.0 );
}

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
x = ( randu()*2.0 ) - 2.0;
y = mycdf( x );
y = mycdf( x[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
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