markov-clustering
v0.0.4
Published
Markov clustering algorithm implementation
Downloads
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Readme
What is this?
This is a simple Markov graph cluster algorithm implementation. For more information about the algorithm, see http://micans.org/mcl/.
Installation
npm install markov-clustering
Usage
The main entry point is the cluster function. It takes two arguments, an adjacency matrix graph representation and an optional options parameter.
Here's an example options object with default values:
const options = {
expandFactor: 2,
inflateFactor: 2,
maxLoops: 10,
multFactor: 1;
}
Example
The undirected graph below is used in this example.
Create an adjacency matrix representation of your graph, this will be the input for the clustering algorithm.
Here's the adjacency matrix for the graph above:
[[0, 1, 1, 0, 0, 0],
[1, 0, 1, 0, 0, 0],
[1, 1, 0, 1, 0, 0],
[0, 0, 1, 0, 1, 1],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 1, 1, 0]]
The following snippet clusters the adjacency matrix:
const mc = require('markov-clustering');
const math = require('mathjs');
const A = math.matrix([[0, 1, 1, 0, 0, 0],
[1, 0, 1, 0, 0, 0],
[1, 1, 0, 1, 0, 0],
[0, 0, 1, 0, 1, 1],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 1, 1, 0]]);
console.log(mc.cluster(A));
$ node snippet.js
[ [ 0, 1, 2 ], [ 3, 4, 5 ] ]
Tests
Some basic tests are included:
npm run test
Dependencies
The implementation relies on http://mathjs.org/ for matrix implementation.
Credits
The implementation is largely based on Python MCL https://github.com/koteth/python_mcl.
License
MIT