https://github.com/mikolalysenko/cuthill-mckee

Bandwidth reducing preconditioner for sparse matrices
https://github.com/mikolalysenko/cuthill-mckee

Last synced: about 2 months ago
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Bandwidth reducing preconditioner for sparse matrices

• Host: GitHub
• URL: https://github.com/mikolalysenko/cuthill-mckee
• Owner: mikolalysenko
• License: mit
• Created: 2015-12-20T18:54:46.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2015-12-20T18:56:06.000Z (about 9 years ago)
• Last Synced: 2024-10-20T14:27:56.461Z (2 months ago)
• Language: JavaScript
• Size: 238 KB
• Stars: 6
• Watchers: 4
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
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