stdlib numerica
An interactive platform for stdlib's numerical computing libraries. Explore statistical distributions, BLAS and LAPACK operations, and random sampling all running directly in your browser.
Explore Scientific Modules
Four interactive modules showcasing stdlib's numerical computing capabilities — all running directly in your browser.
Statistical Distributions
Explore PDF and CDF curves for Normal, Exponential, Beta, Gamma, Chi-squared, and Uniform distributions — all powered by @stdlib/stats.
Explore →BLAS Operations
Level 1 and Level 2 BLAS routines: DGEMV matrix-vector multiply, DAXPY, DDOT, DSCAL, DNRM2 — all from @stdlib/blas/base.
Explore →LAPACK Operations
Real LAPACK routines: matrix copy (dlacpy), row permutations (dlaswp), scaled norms (dlassq), tridiagonal factorization (dpttrf), and machine parameters (dlamch).
Explore →Random Sampling
Generate samples with stdlib PRNGs (randu, randn, minstd, minstd-shuffle) and compare empirical histograms against theoretical PDFs.
Explore →Why stdlib?
stdlib is the most comprehensive standard library for JavaScript and Node.js, providing robust, high-performance implementations of mathematical, statistical, and scientific computing functions.
High Performance
Optimized C/Fortran via native bindings and WebAssembly
Precision
IEEE 754 compliant with rigorous numerical accuracy
Modular
3,500+ individually installable packages
Well Tested
Extensive test suites with reference implementations
How to Install
Getting started with stdlib is as easy as installing any other npm package. You can install individual packages or the entire library.
npm install @stdlib/stdlib
// Or install individual packages for smaller bundles
npm install @stdlib/stats-base-dists-normal-pdf
npm install @stdlib/lapack-base-dlacpy
Basic Example:
// Evaluate the error function
const y = erf( 0.5 );
console.log( y ); // => 0.5204998778130465