FACTORIZE

Algorithm 930, FACTORIZE: an object-oriented linear system solver for MATLAB. The MATLAB TM backslash (x=A∖b) is an elegant and powerful interface to a suite of high-performance factorization methods for the direct solution of the linear system Ax=b and the least-squares problem min x ∥b-Ax∥. It is a meta-algorithm that selects the best factorization method for a particular matrix, whether sparse or dense. However, the simplicity and elegance of its single-character interface prohibits the reuse of its factorization for subsequent systems. Requiring MATLAB users to find the best factorization method on their own can lead to suboptimal choices; even MATLAB experts can make the wrong choice. Furthermore, naive MATLAB users have a tendency to translate mathematical expressions from linear algebra directly into MATLAB, so that x=A -1 b becomes the inferior yet all-to-prevalent x=inv(A)*b. To address these issues, an object-oriented FACTORIZE method is presented. Via simple-to-use operator overloading, solving two linear systems can be written as F=factorize(A); x=F∖b; y=F∖c, where A is factorized only once. The selection of the best factorization method (LU, Cholesky, LDL T , QR, or a complete orthogonal decomposition for rank-deficient matrices) is hidden from the user. The mathematical expression x=A -1 b directly translates into the MATLAB expression x=inverse(A)*b, which does not compute the inverse at all, but does the right thing by factorizing A and solving the corresponding triangular systems.

This software is also peer reviewed by journal TOMS.

References in zbMATH (referenced in 1 article )

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  1. Davis, Timothy A.: Algorithm 930, FACTORIZE: an object-oriented linear system solver for MATLAB (2013)