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cuthill-mckee
Advanced tools
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:
var coeffs = [
[0, 0, 1],
[0, 2, 3],
[1, 1, 1],
[2, 2, 1]
]
var perm = require('cuthill-mckee')(coeffs, 3)
console.log(perm)
npm i cuthill-mckee
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 coefficeintsn
is the number of rows & columns in the matrixReturns A permutation encoded as an array which preconditions the matrix.
(c) 2015 Mikola Lysenko. MIT
FAQs
A bandwidth reducing preconditioner for sparse matrices
The npm package cuthill-mckee receives a total of 775 weekly downloads. As such, cuthill-mckee popularity was classified as not popular.
We found that cuthill-mckee demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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