diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/ctor/benchmark/benchmark.js index c8ef2f798323..1a7e35fbcf6f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/logistic/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/ctor/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var Float64Array = require( '@stdlib/array/float64' ); -var uniform = require( '@stdlib/random/base/uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -33,22 +32,20 @@ var Logistic = require( './../lib' ); bench( pkg+'::instantiation', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var i; - len = 100; - mu = new Float64Array( len ); - s = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - mu[ i ] = uniform( EPS, 10.0 ); - s[ i ] = uniform( EPS, 10.0 ); - } + opts = { + 'dtype': 'float64' + }; + mu = uniform( 100, EPS, 10.0, opts ); + s = uniform( 100, EPS, 10.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist = new Logistic( mu[ i % len ], s[ i % len ] ); + dist = new Logistic( mu[ i % mu.length ], s[ i % s.length ] ); if ( !( dist instanceof Logistic ) ) { bm.fail( 'should return a distribution instance' ); } @@ -89,7 +86,7 @@ bench( pkg+'::get:mu', function benchmark( bm ) { bench( pkg+'::set:mu', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var y; @@ -98,16 +95,16 @@ bench( pkg+'::set:mu', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - y = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - y[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + y = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = y[ i % len ]; - if ( dist.mu !== y[ i % len ] ) { + dist.mu = y[ i % y.length ]; + if ( dist.mu !== y[ i % y.length ] ) { bm.fail( 'should return set value' ); } } @@ -147,7 +144,7 @@ bench( pkg+'::get:s', function benchmark( bm ) { bench( pkg+'::set:s', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var y; @@ -156,16 +153,16 @@ bench( pkg+'::set:s', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - y = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - y[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + y = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.s = y[ i % len ]; - if ( dist.s !== y[ i % len ] ) { + dist.s = y[ i % y.length ]; + if ( dist.s !== y[ i % y.length ] ) { bm.fail( 'should return set value' ); } } @@ -179,7 +176,7 @@ bench( pkg+'::set:s', function benchmark( bm ) { bench( pkg+':entropy', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -189,15 +186,15 @@ bench( pkg+':entropy', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.entropy; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -213,7 +210,7 @@ bench( pkg+':entropy', function benchmark( bm ) { bench( pkg+':kurtosis', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -223,15 +220,15 @@ bench( pkg+':kurtosis', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.kurtosis; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -247,7 +244,7 @@ bench( pkg+':kurtosis', function benchmark( bm ) { bench( pkg+':mean', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -257,15 +254,15 @@ bench( pkg+':mean', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.mean; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -281,7 +278,7 @@ bench( pkg+':mean', function benchmark( bm ) { bench( pkg+':median', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -291,15 +288,15 @@ bench( pkg+':median', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.median; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -315,7 +312,7 @@ bench( pkg+':median', function benchmark( bm ) { bench( pkg+':mode', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -325,15 +322,15 @@ bench( pkg+':mode', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( 1.0 + EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS + 1.0, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.mode; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -349,7 +346,7 @@ bench( pkg+':mode', function benchmark( bm ) { bench( pkg+':skewness', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -359,15 +356,15 @@ bench( pkg+':skewness', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.skewness; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -383,7 +380,7 @@ bench( pkg+':skewness', function benchmark( bm ) { bench( pkg+':stdev', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -393,15 +390,15 @@ bench( pkg+':stdev', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS + 1.0, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.stdev; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -417,7 +414,7 @@ bench( pkg+':stdev', function benchmark( bm ) { bench( pkg+':variance', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -427,15 +424,15 @@ bench( pkg+':variance', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( EPS, 100.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.mu = x[ i % len ]; + dist.mu = x[ i % x.length ]; y = dist.variance; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -451,7 +448,7 @@ bench( pkg+':variance', function benchmark( bm ) { bench( pkg+':cdf', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -461,15 +458,15 @@ bench( pkg+':cdf', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( -3.0, 3.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, -3.0, 3.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.cdf( x[ i % len ] ); + y = dist.cdf( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -484,7 +481,7 @@ bench( pkg+':cdf', function benchmark( bm ) { bench( pkg+':logcdf', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -494,15 +491,15 @@ bench( pkg+':logcdf', function benchmark( bm ) { mu = 1.0; s = 2.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( -3.0, 3.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, -3.0, 3.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.logcdf( x[ i % len ] ); + y = dist.logcdf( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -517,7 +514,7 @@ bench( pkg+':logcdf', function benchmark( bm ) { bench( pkg+':logpdf', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -527,15 +524,15 @@ bench( pkg+':logpdf', function benchmark( bm ) { mu = 1.0; s = 2.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( -3.0, 3.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, -3.0, 3.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.logpdf( x[ i % len ] ); + y = dist.logpdf( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -550,7 +547,7 @@ bench( pkg+':logpdf', function benchmark( bm ) { bench( pkg+':mgf', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -560,15 +557,15 @@ bench( pkg+':mgf', function benchmark( bm ) { mu = 2.0; s = 0.2; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( 0.0, 1.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.mgf( x[ i % len ] ); + y = dist.mgf( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -583,7 +580,7 @@ bench( pkg+':mgf', function benchmark( bm ) { bench( pkg+':pdf', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -593,15 +590,15 @@ bench( pkg+':pdf', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( -3.0, 3.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, -3.0, 3.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.pdf( x[ i % len ] ); + y = dist.pdf( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -616,7 +613,7 @@ bench( pkg+':pdf', function benchmark( bm ) { bench( pkg+':quantile', function benchmark( bm ) { var dist; - var len; + var opts; var mu; var s; var x; @@ -626,15 +623,15 @@ bench( pkg+':quantile', function benchmark( bm ) { mu = 2.0; s = 3.0; dist = new Logistic( mu, s ); - len = 100; - x = new Float64Array( len ); - for ( i = 0; i < len; i++ ) { - x[ i ] = uniform( 0.0, 1.0 ); - } + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, opts ); bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = dist.quantile( x[ i % len ] ); + y = dist.quantile( x[ i % x.length ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); }