I don't find an ng on numerical computation, and I use
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
I don't find an ng on numerical computation, and I use
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
I don't find an ng on numerical computation, and I use
Fortran, so I ask here:
On Sat, 18 Nov 2023 16:29:08 +0100, db <dieterhansbritz@gmail.com>
wrote:
I don't find an ng on numerical computation, and I use
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
The following link to LAPACK says it is written in Fortran 90: https://www.netlib.org/lapack/
There is a link on that page to browse and download the routines.
db <dieterhansbritz@gmail.com> wrote:Thanks. Wow, Algol, my first high-level language after one called A9,
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
Um, how big are the matrices and what are you doing? For
analysis of very large datasets, people are using
randomized linear algebraic methods to extract
eigenvalues/vectors very quickly and accurately -
SciPy's scipy.linalg.interpolative calls a Fortran
library (it's still F77 ;)) from here:
http://tygert.com/software.html
which in turn uses LAPACK. The resulting Singular Value
Decomposition (https://arxiv.org/pdf/2302.11474.pdf) has
the bits you want. For my smaller problems, I use EISPACK,
translated from Algol of the 1960's...
Cheers, David Duffy.
On Sat, 18 Nov 2023 16:29:08 +0100Ah, thanks. I had searched for "numerical"...
db <dieterhansbritz@gmail.com> wrote:
I don't find an ng on numerical computation, and I use
Fortran, so I ask here:
There does exist sci.math.num-analysis .It has a lot of spam but if
you access it through a server which filters spam (or you do your own filtering) , it's ok. Non spam posts seem at present to only be
conference announcements. For future numerical analysis questions you
could try crossposting to sci.math.num-analysis and comp.lang.fortran .
I don't find an ng on numerical computation, and I use
Fortran, so I ask here: what is a good routine for
computing eigenvalues and -vectors? I have an old
version of RGG but am not happy with it. Is there
something better?
I anticipate the question, why am I unhappy with RGG?
Among other things, it's an old f77 routine.
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