Very nice!

I find those algorithms could make it into uBlas like "extensions", yourself and maintainers permitting of course. It could save a lot of people the time to reinvent them or the need to bind to external libraries. What do all think?

I use my custom algorithms in some cases, and I was looking into reimplementing JAMA, but never had the time. Nice work Fredric.

Best
Nasos


> From: frederic.devernay@inrialpes.fr
> Date: Fri, 30 Apr 2010 15:48:22 +0200
> To: ublas@lists.boost.org
> Subject: [ublas] announcement: ublasJama (ublas port of Jama, including SVD and eigenvalue decomposition)
>
> Hi,
>
> I translated Jama to ublas, mainly because I needed SVD. It's not optimal nor generic, but at least it's here. Note that the bug in the Jama SVD was fixed too.
>
> cat flames > /dev/null
>
> Fred
>
> Download it from http://devernay.free.fr/hacks/ublasJama.html
>
> * What is ublasJama?
>
> ublasJama is translation of the public domain Jama (Java Matrix Package) to C++ using boost.ublas for the linear algebra. Jama itself is a Java implementation of algorithms for dense matrices found in LINPACK and EISPACK.
>
> Author of the ublas translation: Frederic Devernay .
>
> Documentation: see the Jama documentation.
>
> Original Authors: see the Jama list of authors.
>
> No optimization of the original code was done, but the functionality is here:
>
> • Cholesky Decomposition of symmetric, positive definite matrices
> • LU Decomposition (Gaussian elimination) of rectangular matrices
> • QR Decomposition of rectangular matrices
> • Eigenvalue Decomposition of both symmetric and nonsymmetric square matrices
> • Singular Value Decomposition of rectangular matrices
> There are two test programs:
>
> • TestMatrix, in subdirectory test - the original Jama tests, where only the relevant tests were kept.
> • MagicSquareExample, in subdirectory examples
>
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> Sent to: nasos_i@hotmail.com

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