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View graph data structures in the IPython notebook.

Project description


An embeddable webGL graph visualization library.


* [IPython notebook](
* [les misérables](
* [github connections](


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:


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

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

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.

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