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Re: trired/triql and EOF/PCA [message #28975] Sat, 26 January 2002 09:58 Go to next message
the_cacc is currently offline  the_cacc
Messages: 104
Registered: October 2001
Senior Member
wmc@bas.ac.uk wrote in message news:<3c512bf9@news.nwl.ac.uk>...
> ..finding eigenvectors of a symmetric matrix.

I'm no expert on eigenvalue decomposition but I think singular value
decomposition may be related (IDL routine "SVDC"). Pre-IDL 5.4, this
had the no. of iterations hard-coded to be 20 so it fell down for
moderate matrix sizes. Now there is an ITMAX keyword, which lets you
set the max. no. of iterations. If you hassle IDL customer support you
*may* be able to persuade them to provide such a keyword in the
TRIRED/TRIQL functions. But that's for the future... As for doing
partial decompositions, I don't think IDL has one.

Ciao.
Re: trired/triql and EOF/PCA [message #28981 is a reply to message #28975] Fri, 25 January 2002 10:06 Go to previous messageGo to next message
k-bowman is currently offline  k-bowman
Messages: 12
Registered: December 2001
Junior Member
In article <3c512bf9@news.nwl.ac.uk>, wmc@bas.ac.uk wrote:

> 'm trying to to EOF (=PCA) analysis, which involvees finding eigenvectors
> of a symmetric matrix. I use trired/triql (should I?). This works fine for
> small matrices but on large ones (well not very large... 500x500, perhaps)
> falls over with "too many iterations". But... there is no "how many
> iterations" parameter to set. Ideas?

I think you will be forced to use external libraries. LAPACK includes a number of robust eigenfunction routines and is free. I used LAPACK recently, and it was easier to write a short Fortran code than to link the LAPACK routines into IDL.

See, for example,

http://www.netlib.no/netlib/lapack/

or

http://www.cs.colorado.edu/~lapack/.

Ken
Re: trired/triql and EOF/PCA [message #29067 is a reply to message #28975] Sun, 27 January 2002 15:18 Go to previous message
the_cacc is currently offline  the_cacc
Messages: 104
Registered: October 2001
Senior Member
Check this thread for discussion on the topic "SVD vs PCA":

http://groups.google.com/groups?hl=en&threadm=5e0lod%247 cr%40mozo.cc.purdue.edu&rnum=4&prev=/groups%3Fsource id%3Dnavclient%26q%3D%253A%2BSubrata%2BChatterjee%2Bprincipa l
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