npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

ml-fcnnls

v3.0.0

Published

Fast Combinatorial Non-negative Least Squares

Downloads

1,413

Readme

fcnnls

NPM version build status Test coverage npm download DOI

Fast Combinatorial Non-negative Least Squares.

As described in the publication by Van Benthem and Keenan (10.1002/cem.889), which is in turn based on the active-set method algorithm previously published by Lawson and Hanson. The basic active-set method is implemented in the nnls repository.

Given the matrices $\mathbf{X}$ and $\mathbf{Y}$, the code finds the matrix $\mathbf{K}$ that minimises the squared Frobenius norm $$\mathrm{argmin}_K ||\mathbf{XK} -\mathbf{Y}||^2_F$$ subject to $\mathbf{K}\geq 0$.

https://en.wikipedia.org/wiki/Non-negative_least_squares

Installation

npm i ml-fcnnls

Usage Example

  1. Single $y$, using arrays as inputs.
import { fcnnlsVector } from 'ml-fcnnls';

const X = [
  [1, 1, 2],
  [10, 11, -9],
  [-1, 0, 0],
  [-5, 6, -7],
];
const y = [-1, 11, 0, 1];

const k = fcnnlsVector(X, y).K.to1DArray();
/* k = [0.4610, 0.5611, 0] */
  1. Multiple RHS, using Matrix instances as inputs.
import { fcnnls } from 'ml-fcnnls';
import { Matrix } from 'ml-matrix'; //npm i ml-matrix

// Example with multiple RHS

const X = new Matrix([
  [1, 1, 2],
  [10, 11, -9],
  [-1, 0, 0],
  [-5, 6, -7],
]);

// Y can either be a Matrix or an array of arrays
const Y = new Matrix([
  [-1, 0, 0, 9],
  [11, -20, 103, 5],
  [0, 0, 0, 0],
  [1, 2, 3, 4],
]);

const K = fcnnls(X, Y).K;
// `K.to2DArray()` converts the matrix to array.
/*
K = Matrix([
  [0.4610, 0, 4.9714, 0],
  [0.5611, 0, 4.7362, 2.2404],
  [0, 1.2388, 0, 1.9136],
])
*/
  1. Using the options
const K = fcnnls(X, Y, {
  info: true, // returns the error/iteration.
  maxIterations: 5,
  gradientTolerance: 0,
});
/* same result than 2*/

API Documentation

License

MIT