cuthill-mckee
=============
The reverse Cuthill-Mckee method is a fast and effective preconditioner for reducing the bandwidth of sparse linear systems. When solving a positive semidefinite linear system using Cholesky factorization, it greatly reduces fill-in. For example, here is the Laplacian matrix of the Stanford bunny:

BEFORE:

AFTER:

example

``javacript
var coeffs = [
[0, 0, 1],
[0, 2, 3],
[1, 1, 1],
[2, 2, 1]
]

var perm = require('cuthill-mckee')(coeffs, 3)

console.log(perm)
`

install

npm i cuthill-mckee

usage

#### require('cuthill-mckee')(list, n)
This module takes the coefficients of a sparse matrix as input and gives permutation which reduces the fill-in (or bandwidth) of the matrix.

* list is a list of matrix coefficeints
* n` is the number of rows & columns in the matrix

Returns A permutation encoded as an array which preconditions the matrix.

license

(c) 2015 Mikola Lysenko. MIT