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Original file line number Diff line number Diff line change
Expand Up @@ -21,10 +21,10 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pkg = require( './../package.json' ).name;
var cdf = require( './../lib' );
var uniform = require('@stdlib/random/base/uniform')


// MAIN //
Expand All @@ -36,12 +36,13 @@ bench( pkg, function benchmark( b ) {
var y;
var i;

q = uniform( 0.0, 12.0 );
r = uniform( 2.0, 20.0 );
v = uniform( 2.0, 20.0 );
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Here, q, r, and v should each be a Float64Array of length 100 and should be initialized in a loop. Reference PRs will help.

y = cdf( q, r, v );
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This should still remain in the benchmarking loop, as it is the part being benchmarked.


b.tic();
for ( i = 0; i < b.iterations; i++ ) {
q = randu() * 12.0;
r = ( randu()*20.0 ) + 2.0;
v = ( randu()*20.0 ) + 2.0;
y = cdf( q, r, v );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand All @@ -65,11 +66,11 @@ bench( pkg+':factory', function benchmark( b ) {
v = 5.0;
r = 3.0;
mycdf = cdf.factory( v, r );
q = uniform( 0.0, 1.0 );
y = mycdf( q );
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Same comment as above and applies throughout the PR.

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std
Is this the right approach ?

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Yes, considering you are using the correct range for random number generation.


b.tic();
for ( i = 0; i < b.iterations; i++ ) {
q = randu();
y = mycdf( q );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -21,10 +21,10 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pkg = require( './../package.json' ).name;
var quantile = require( './../lib' );
const uniform = require('@stdlib/random/base/uniform');


// MAIN //
Expand All @@ -36,12 +36,13 @@ bench( pkg, function benchmark( b ) {
var y;
var i;

p = uniform( 0.0, 1.0 );
r = uniform( 2.0, 20.0 );
v = uniform( 2.0, 20.0 );
y = quantile( p, r, v );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
p = randu();
r = ( randu()*20.0 ) + 2.0;
v = ( randu()*20.0 ) + 2.0;
y = quantile( p, r, v );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand All @@ -65,11 +66,11 @@ bench( pkg+':factory', function benchmark( b ) {
v = 5.0;
r = 3.0;
myquantile = quantile.factory( v, r );
p = uniform( 0.0, 1.0 );
y = myquantile( p );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
p = randu();
y = myquantile( p );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand Down