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