R-alpha: Eigenvalue Computation Query
Mon, 19 May 1997 07:50:16 +1200 (NZST)
I have been looking at the "eigen" function and have reintroduced the
ability to compute (right) eigenvalues and vectors for non-symmetric
matrices. I've also made "eigen" complex capable.
The code is based on the eispack entry points RS, RG, CH, CG (which is
what S appears to use too). The problem with both the S and R
implementations is that they consume huge amounts of memory. Some of
this is due to purely ".Fortran" overhead, which I think I can cure.
But some of the bloat is due to the inclusion of special eigenvalues-only
code from eispack.
The question is:
Should I drop this special code and always compute both eigenvalues
and eigenvectors? This would substantially reduce code size, but might
increase computational cost in the case where only eigenvalues are
PS: For the lapack fans out there ... I looked hard at using lapack
as an alternative to eispack, but it's written in a fashion which
does not make its addition to R as simple as linpack and eispack.
When we all have SMP desktop machines it will become more of an issue.
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