Awesome
ndarray-lup-solve
Solve ndarray Ax=b via LU factorization with pivoting
Introduction
Given an LUP factorization, this module solves for x in Ax = b. More precisely, it solves for x in LUx = Pb.
Example
var lup = require('ndarray-lup-factorization'),
solve = require('ndarray-lup-solve'),
ndarray = require('ndarray'),
pool = require('ndarray-scratch')
var A = ndarray([2,1,1,0, 4,3,3,1, 8,7,9,5, 6,7,9,8], [4,4])
var b = ndarray([13,38,102,107])
var P = []
// In-place LUP factorization:
// Note: repeated A tells it L and U are both stored in A
lup(A, A, P)
solve( A, A, P, b)
// b now contains the answer x: [2,5,4,3]
// A and P are unchanged and can be re-used to solve another problem
Usage
require('ndarray-lup-solve')( L, U, P, b [, work] )
L
: The n x n ndarray lower-triangular portion of the LUP factorization. The diagonal entries are implicitly assumed to be 1. Unchanged by the algorithm.U
: The n x n ndarray upper-triangular portion of the LUP factorization. Unchanged by the algorithm.P
: AnArray
of length n containg the permutationb
: An ndarray of length n containing the righthand side of Ax = bwork
: (optional) A vector used to permute the entries. If not provided, it is allocated and released into anndarray-scratch
typed vector pool.
Returns true
on successful completion; false
otherwise.
require('ndarray-lup-solve')( LU, LU, P, b [, work] )
If the first two arguments are identical then it's understood that both L and U are stored in a single matrix with the diagonal entries of L (all unity) omitted. Usage and behavior is otherwise identical.
Credits
(c) 2015 Ricky Reusser. MIT License