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

@rantanen/igraph

v0.1.0

Published

An embeddable webGL graph visualization library.

Downloads

3

Readme

igraph

An embeddable webGL graph visualization library. http://patrickfuller.github.io/igraph/

Examples

IPython

The IPython notebook is an open-source tool poised to replace MATLAB in many applications. As a scientist of sorts, I'm all about it. Therefore, I made handles to use igraph with the notebook. Install through pip:

pip install igraph

Open a new notebook and test the setup by typing:

import igraph
igraph.draw([(1, 2), (2, 3), (3, 4), (4, 1), (4, 5), (5, 2)])

into a notebook cell. You should get a paddlewheel graph as an output. You can use this in conjunction with other code for educational purposes (try generating a red-black tree!). There are three commands and some optional parameters to check out. Read the docstrings and check out the associated example for more.

Javascript

Start by downloading the minified javascript file:

wget https://raw.githubusercontent.com/patrickfuller/igraph/master/js/build/igraph.min.js

Include this file alongside jQuery in your project, and then use with:

igraph.create('my-selector');
igraph.draw(myGraph);

where 'my-selector' is where you want to place igraph, and myGraph is a plain ol' object. See below for more on the object structure, or just check out the included example. The igraph.create() method takes a few optional parameters, specifying the sizes and colors of nodes, as well as force-directed optimization.

options = {
    directed: true, // Toggles edge arrows
    nodeSize: 2.0, // Default node size
    edgeSize: 0.25, // Edge connection diameter
    arrowSize: 1.0, // If drawn, edge arrow size
    defaultNodeColor: 0xaaaaaa, // Color for nodes without a "color" property
    defaultEdgeColor: 0x777777, // Color for edges without a "color" property
    shader: "toon", // three.js shader to use, can be "toon", "basic", "phong", or "lambert"
    runOptimization: true // Runs a force-directed-layout algorithm on the graph
};

Graph Data Format

igraph takes input graph data structures as plain objects. Here's the most boring graph in the world:

{
    nodes: {
        jane: { },
        bob: { },
        mike: { },
        sally: { }
    },
    edges: [
        { source: "jane", target: "bob" },
        { source: "bob", target: "mike" },
        { source: "mike", target: "sally" }
    ]
}

Nodes require no information outside of their keys. However, there are useful optional parameters that can be specified.

{
    color: 0xffffff, // Color for this node
    size: 1.0, // Scaling factor for this node's size
    location: [0.0, 0.0, 0.0] // Starting location of node. Useful for pre-rendering.
}

By default, the algorithm runs a force-directed layout on the graph. When enabled, the "location" field is optional. However, for larger graphs, you will want to disable this feature and pre-render the locations. Use the associated Python library (igraph.generate) to do so.