https://github.com/mikolalysenko/conjugate-gradient

Conjugate gradient solver for JavaScript
https://github.com/mikolalysenko/conjugate-gradient

Last synced: about 2 months ago
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Conjugate gradient solver for JavaScript

• Host: GitHub
• URL: https://github.com/mikolalysenko/conjugate-gradient
• Owner: mikolalysenko
• License: mit
• Created: 2013-04-06T16:17:57.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2014-04-03T20:18:27.000Z (over 10 years ago)
• Last Synced: 2024-10-20T14:28:18.890Z (2 months ago)
• Language: JavaScript
• Size: 133 KB
• Stars: 10
• Watchers: 4
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# conjugate-gradient

Solves sparse symmetric positive definite linear systems.  These problems arise in many physical applications, like [linear elasticity](http://en.wikipedia.org/wiki/Linear_elasticity), [heat transfer](http://en.wikipedia.org/wiki/Heat_transfer) and other diffusion based transport phenomena.

This code implements the [conjugate gradient method](http://en.wikipedia.org/wiki/Conjugate_gradient_method) using a [Jacobi preconditioner](http://en.wikipedia.org/wiki/Preconditioner).

## Install

    npm install conjugate-gradient

## Example

```javascript

var pcg = require("conjugate-gradient")

  , CSRMatrix = require("csr-matrix")

//Create a matrix

var A = CSRMatrix.fromDense([[-2, 1, 0],

                             [ 1,-2, 1],

                             [ 0, 1,-2]])

//Create input vector

var B = new Float64Array([1, 0, 0])

//Solve equation:

//

//  A x = B

//

console.log(pcg(A, b))

```

### `require("conjugate-gradient")(A, b[, x0, tolerance, max_iter])`

Solves the equation Ax = b by conjugate gradient

* `A` is a symmetric positive definite matrix represented as a [CSRMatrix](https://github.com/mikolalysenko/csr-matrix)

* `b` is an array of length n

* `x0` is an optional initial guess for the solution to the equation.  If specified, the result of the solution will also get stored in this array

* `tolerance` is a cutoff tolerance for the solution.  (Default is 1e-5)

* `max_iter` is the maximum number of iterations to run the solver.  (Default is min(n, 20))

**Returns** An array encoding the solution to the equation Ax = b

# Credits

(c) 2013 Mikola Lysenko. MIT License