Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

@atomistics/gradient-descent

Package Overview
Dependencies
Maintainers
1
Versions
2
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

@atomistics/gradient-descent

Given a set of atomic positions and a potential energy calculator, provides a function that steps in the direction of the force.

  • 1.0.1
  • latest
  • npm
  • Socket score

Version published
Weekly downloads
3
increased by200%
Maintainers
1
Weekly downloads
 
Created
Source

gradient-descent

Given a set of atomic positions and a potential energy calculator, provides a function that steps in the direction of the force.

npm i --save @atomistics/gradient-descent

Example

const LJ = require('@atomistics/lennard-jones-pairwise-js');
const pairwisePotential = require('@atomistics/pairwise-potential');
const gradientDescent = require('@atomistics/gradient-descent');

// Create a generic LJ potential.
const ljp = pairwisePotential(LJ());

// Initialize gradient descent with a particle at the origin and at 1.2 along x,
// our Lennard-Jones potential, and a timestep of 0.01.
const step = gradientDescent([0,0,0, 1.2,0,0], ljp, 0.01);

// Take ten steps, printing the energy and force at each step.
for (let i = 0; i < 10; i++) {
  const rfe = step();
  console.log(rfe.energy.toFixed(4), norm(rfe.force).toFixed(4));
}

/*  
    Prints the following:
    -0.6639 3.5784
    -0.7973 3.8020
    -0.9332 3.0937
    -0.9982 0.6909
    -0.9998 0.2555
    -1.0000 0.1175
    -1.0000 0.0505
    -1.0000 0.0224
    -1.0000 0.0098
    -1.0000 0.0043    
*/

API

const gradientDescent = require('@atomistics/gradient-descent');
const step = gradientDescent(positions, potential, timestep);
ParameterTypeDescription
positionsfloat arrayAn flat array of atomic positions in 3D
potentialfunctionA potential energy function
OptionTypeDefaultDescription
timestepfloat0.01The coefficient by which the force is multiplied when calculating a distance to step along the negative gradient

Returns a function that when invoked performs a single iteration of the gradient descent algorithm. An internal state is maintained to track the progress of the algorithm.

const result = step();

Returns an object containing the updated energy, force, and positions of the system.

NameTypeDescription
result.energyfloatThe energy of the system as of the most recent step
result.forcefloat arrayA flat array of forces on each component of the system
result.positionsfloat arrayA flat array of the updated atomic positions of the system

Keywords

FAQs

Package last updated on 05 Sep 2018

Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc