feat: refactor random number generation stats/base/dists/weibull

[ShabiShett07]

Resolves #4992

Description

What is the purpose of this pull request?

This pull request:

• Solves the issue [RFC]: Refactor random number generation in JS benchmarks for stats/base/dists/weibull #4992

Related Issues

Does this pull request have any related issues?

This pull request:

• resolves [RFC]: Refactor random number generation in JS benchmarks for stats/base/dists/weibull #4992 [RFC]: Refactor random number generation in JS benchmarks for stats/base/dists (tracking issue) #4993

Questions

Any questions for reviewers of this pull request?

What about the benchmark of ctor? Do we need to change that too?

Other

Any other information relevant to this pull request? This may include screenshots, references, and/or implementation notes.

No.

Checklist

Please ensure the following tasks are completed before submitting this pull request.

• Read, understood, and followed the contributing guidelines.

---

@stdlib-js/reviewers

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/weibull/cdf	$\color{green}222/222$ $\color{green}+100.00\%$	$\color{green}23/23$ $\color{green}+100.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{green}222/222$ $\color{green}+100.00\%$
stats/base/dists/weibull/entropy	$\color{green}126/126$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}126/126$ $\color{green}+100.00\%$
stats/base/dists/weibull/kurtosis	$\color{green}137/137$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}137/137$ $\color{green}+100.00\%$
stats/base/dists/weibull/logcdf	$\color{green}235/235$ $\color{green}+100.00\%$	$\color{green}26/26$ $\color{green}+100.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{green}235/235$ $\color{green}+100.00\%$
stats/base/dists/weibull/logpdf	$\color{green}236/236$ $\color{green}+100.00\%$	$\color{green}33/33$ $\color{green}+100.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{green}236/236$ $\color{green}+100.00\%$
stats/base/dists/weibull/mean	$\color{green}125/125$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}125/125$ $\color{green}+100.00\%$
stats/base/dists/weibull/median	$\color{green}126/126$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}126/126$ $\color{green}+100.00\%$
stats/base/dists/weibull/mgf	$\color{red}262/264$ $\color{green}+99.24\%$	$\color{red}23/25$ $\color{green}+92.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{red}262/264$ $\color{green}+99.24\%$
stats/base/dists/weibull/mode	$\color{green}128/128$ $\color{green}+100.00\%$	$\color{green}10/10$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}128/128$ $\color{green}+100.00\%$
stats/base/dists/weibull/pdf	$\color{green}238/238$ $\color{green}+100.00\%$	$\color{green}34/34$ $\color{green}+100.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{green}238/238$ $\color{green}+100.00\%$
stats/base/dists/weibull/quantile	$\color{green}218/218$ $\color{green}+100.00\%$	$\color{green}23/23$ $\color{green}+100.00\%$	$\color{green}3/3$ $\color{green}+100.00\%$	$\color{green}218/218$ $\color{green}+100.00\%$
stats/base/dists/weibull/skewness	$\color{green}139/139$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}139/139$ $\color{green}+100.00\%$
stats/base/dists/weibull/stdev	$\color{green}128/128$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}128/128$ $\color{green}+100.00\%$
stats/base/dists/weibull/variance	$\color{green}128/128$ $\color{green}+100.00\%$	$\color{green}8/8$ $\color{green}+100.00\%$	$\color{green}1/1$ $\color{green}+100.00\%$	$\color{green}128/128$ $\color{green}+100.00\%$

The above coverage report was generated for the changes in this PR.

[anandkaranubc]

Can you please change the title to:

bench: refactor random number generation in stats/base/dists/weibull

[anandkaranubc]

Also, I am not sure if you have the most recent changes in your current branch. Try to update your branch with the latest changes so you can also apply the required changes to all the benchmark.native.js files. Good luck! :)

[anandkaranubc]

This should be moved outside the benchmarking loops in a different loop before b.tic()

Since random generation is expensive, we don't want it to interfere with the benchmarks. You can see the reference PRs. Also, this change is consistent throughout the whole PR.

[anandkaranubc]

Suggested change

	for ( i = 0; i < len; i++ ) {
	for ( i = 0; i < b.iterations; i++ ) {

The range remains the same.

[anandkaranubc]

Suggested change

	y = cdf( x[ i%len ], k[ i%len ], lambda[ i%len ] );
	y = cdf( x[ i % len ], k[ i % len ], lambda[ i % len ] );

[anandkaranubc]

Suggested change

	x[ i ] = uniform( EPS, 100 );
	x[ i ] = uniform( EPS, 100.0 );

[anandkaranubc]

	lambda = 3.14;
	k = 2.25;
	len = 100
	mycdf = cdf.factory( k, lambda );
	x = new Float64Array( len );
	for ( i = 0; i < len; i++ ) {
		x = uniform( EPS, 100.0 );
	}

	b.tic();
	for ( i = 0; i < b.iterations; i++ ) {
		y = mycdf( x[ i % len ] );

Make sure to follow consistent spacing, following the code conventions.