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cholesky-solve
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This module solves sparse symmetric positive definite linear systems by using the Cholesky decomposition
This module solves sparse symmetric positive definite linear systems,
by finding the Cholesky decomposition(the LDL^T
decomposition, and not
the LL^T
decomposition), and then doing forward substitution and
backward substitution. It is basically a Javascript port of the paper
"Algorithm 8xx: a concise sparse Cholesky factorization package". This
kind of solver has many applications in digital geometry processing.
npm install cholesky-solve
var choleskySolve = require('cholesky-solve')
// matrix dimension.
const n = 10
/*
Below we specify the sparse matrix:
1.7 0 0 0 0 0 0 0 0.13 0
0 1.0 0 0 0.02 0 0 0 0 0.01
0 0 1.5 0 0 0 0 0 0 0
0 0 0 1.1 0 0 0 0 0 0
0 0.02 0 0 2.6 0 0.16 0.09 0.52 0.53
0 0 0 0 0 1.2 0 0 0 0
0 0 0 0 0.16 0 1.3 0 0 0.56
0 0 0 0 0.09 0 0 1.6 0.11 0
0.13 0 0 0 0.52 0 0 0.11 1.4 0
0 0.01 0 0 0.53 0 0.56 0 0 3.1
Note that we only specify the coefficients on the diagonal,
or above the diagonal. Since the matrix is symmetric,
specifying the coefficients below the diagonal is completely redundant.
Finally, the order in which the coefficients is specified in is not important.
*/
// the sparse matrix on left-hand side.
var M = [
[2, 2, 1.5],
[1, 1, 1.0],
[1, 4, 0.02],
[5, 5, 1.2],
[7, 7, 1.6],
[4, 4, 2.6],
[3, 3, 1.1],
[4, 7, 0.09],
[4, 6, 0.16],
[0, 0, 1.7],
[4, 8, 0.52],
[0, 8, 0.13],
[6, 6, 1.3],
[7, 8, 0.11],
[4, 9, 0.53],
[8, 8, 1.4],
[9, 9, 3.1],
[1, 9, 0.01],
[6, 9, 0.56]
]
// right-hand side
var b = [0.287, 0.22, 0.45, 0.44, 2.486, 0.72, 1.55, 1.424, 1.621, 3.759]
var P = require('cuthill-mckee')(M, n)
// finally, solve the equation
// Mx = b
// and print x
// the `prepare` method returns a function that can be used to solve
// the equation for any value of b.
var solve = choleskySolve.prepare(M, n, P)
console.log(solve(b))
require("cholesky-solve").prepare(M, n, [P])
Decomposes M
into the Cholesky decomposition of the form LDL^T
. A
function is returned that can be used to solve the equation Mx = b
,
for some given value of b
.
M
a list of the matrix coefficients of the sparse matrix M
. These are
the coefficients on the diagonal and above the diagonal. The ones below the
diagonal do not need to be specified, since the matrix is symmetric.n
the dimension of the matrix M
P
encodes a permutation matrix that preconditions M
before the Cholesky decomposition is solved for. A possible algorithm for finding a good permutation is
Cuthill–McKee. See
the module cuthill-mckee for a
Javascript implementation.Returns A function that takes a single argument b
. The function
returns the solution to the equation Mx = b
, encoded as a simple array.
NOTE the module does no sanity checking on the input arguments. It is assumed that the user knows what he/she is doing!
FAQs
This module solves sparse symmetric positive definite linear systems by using the Cholesky decomposition
The npm package cholesky-solve receives a total of 10 weekly downloads. As such, cholesky-solve popularity was classified as not popular.
We found that cholesky-solve 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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