An embeddable webGL graph visualization library. http://luizhnlorena.github.io/jgraph/

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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 jgraph with the notebook. Install through pip:

pip install jgraph

Open a new notebook and test the setup by typing:

import jgraph
jgraph.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.

You can install through npm:

npm install jgraph

Once installed, you can use with:

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

where 'my-selector' is where you want to place jgraph, and myGraph is a javascript object. See below for more on the object structure, or just check out the included example. The jgraph.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
};

jgraph 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 (jgraph.generate) to do so.