Editing Cholesky decomposition (section)

== Implementations in programming libraries ==
* [[C programming language]]: the [[GNU Scientific Library]] provides several implementations of Cholesky decomposition.
* [[Maxima (software)|Maxima]] computer algebra system: function <code>cholesky</code> computes Cholesky decomposition.
* [[GNU Octave]] numerical computations system provides several functions to calculate, update, and apply a Cholesky decomposition.
* The [[LAPACK]] library provides a high performance implementation of the Cholesky decomposition that can be accessed from [[Fortran]], [[C (programming language)|C]] and most languages.
* In [[Python (programming language)|Python]], the function <code>cholesky</code> from the <code>numpy.linalg</code> module performs Cholesky decomposition.
* In [[Matlab]], the <code>chol</code> function gives the Cholesky decomposition. Note that <code>chol</code> uses the upper triangular factor of the input matrix by default, i.e. it computes <math display=inline>A = R^* R</math> where <math display=inline>R</math> is upper triangular. A flag can be passed to use the lower triangular factor instead.
* In [[R (programming language)|R]], the <code>chol</code> function gives the Cholesky decomposition.
* In [[Julia (programming language)|Julia]], the <code>cholesky</code> function from the <code>LinearAlgebra</code> standard library gives the Cholesky decomposition.
* In [[Mathematica]], the function "<code>CholeskyDecomposition</code>" can be applied to a matrix.
* In [[C++]], multiple linear algebra libraries support this decomposition:
** The [[Armadillo (C++ library)]] supplies the command <code>chol</code> to perform Cholesky decomposition. 
** The [[Eigen (C++ library)|Eigen library]] supplies Cholesky factorizations for both sparse and dense matrices.
** In the [[ROOT]] package, the <code>TDecompChol</code> class is available. 

* In [[Analytica (software)|Analytica]], the function <code>Decompose</code> gives the Cholesky decomposition.
* The [https://commons.apache.org/proper/commons-math/commons-math-docs/apidocs/org/apache/commons/math4/legacy/linear/CholeskyDecomposition.html Apache Commons Math library has an implementation] which can be used in Java, Scala and any other JVM language.