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bench: update array initialisation and refactor to use string interpolation in stats/anova1 #10199

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bench: update array initialisation and refactor to use string interpolation in stats/anova1 #10199

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36 changes: 16 additions & 20 deletions lib/node_modules/@stdlib/stats/anova1/benchmark/benchmark.js
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Original file line number Diff line number Diff line change
Expand Up @@ -21,10 +21,11 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
var uniform = require( '@stdlib/random/array/uniform' );
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var isObject = require( '@stdlib/assert/is-object' );
var isString = require( '@stdlib/assert/is-string' ).isPrimitive;
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var anova1 = require( './../lib' );

Expand All @@ -35,20 +36,17 @@ bench( pkg, function benchmark( b ) {
var result;
var group;
var vals;
var len;
var i;

vals = new Array( 100 );
group = new Array( 100 );
len = vals.length;
for ( i = 0; i < len; i++ ) {
group[ i ] = discreteUniform( 0, 3 );
vals[ i ] = ( randu()*50.0 ) + ( 10.0*group[ i ] );
}
group = discreteUniform( 100, 0.0, 3.0, {
'dtype': 'generic'
});
vals = uniform( 100, 0.0, 100.0, {
'dtype': 'generic'
});

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
vals[ i % vals.length ] = ( randu()*50.0 ) + ( 10.0*group[ i ] );
result = anova1( vals, group );
if ( typeof result !== 'object' ) {
b.fail( 'should return an object' );
Expand All @@ -62,22 +60,20 @@ bench( pkg, function benchmark( b ) {
b.end();
});

bench( pkg+':print', function benchmark( b ) {
bench( format( '%s:print', pkg ), function benchmark( b ) {
var digits;
var result;
var output;
var group;
var vals;
var len;
var i;

vals = new Array( 100 );
group = new Array( 100 );
len = vals.length;
for ( i = 0; i < len; i++ ) {
group[ i ] = discreteUniform( 0, 3 );
vals[ i ] = ( randu()*50.0 ) + ( 10.0*group[ i ] );
}
vals = uniform( 100, 0.0, 100.0, {
'dtype': 'generic'
});
group = discreteUniform( 100, 0.0, 3.0, {
'dtype': 'generic'
});
result = anova1( vals, group );

b.tic();
Expand Down