mark wrote: > Sorry for joining this discussion late. > If you are only interested in the four largest eigenvalues, there are > more efficient algorithms out there than just eig(). > There are algorithms that just give you the N largest. > Then again, I don't know of any Python implementations, but I haven't > looked, > Mark > > On Apr 29, 11:04 pm, "Matthieu Brucher" <[EMAIL PROTECTED]> > wrote: > >> 2007/4/29, Anton Sherwood <[EMAIL PROTECTED]>: >> >> >> >> >> >> >>>> Anton Sherwood wrote: >>>> >>>>> I'm using eigenvectors of a graph's adjacency matrix as "topological" >>>>> coordinates of the graph's vertices as embedded in 3space (something I >>>>> learned about just recently). Whenever I've done this with a graph >>>>> >>> that >>> >>>>> *does* have a good 3d embedding, using the first eigenvector results >>>>> >>> in >>> >>>>> a flat model: apparently the first is not independent, at least in >>>>> >>> such >>> >>>>> cases. . . . >>>>> >>> Charles R Harris wrote: >>> >>>> . . . the embedding part sounds interesting, >>>> I'll have to think about why that works. >>>> >>> It's a mystery to me: I never did study enough matrix algebra to get a >>> feel for eigenvectors (indeed this is the first time I've had anything >>> to do with them). >>> >>> I'll happily share my code with anyone who wants to experiment with it. >>> >> Seems to me that this is much like Isomap and class multidimensional >> scaling, no ? >> >> Matthieu >> >> _______________________________________________ >> Numpy-discussion mailing list >> [EMAIL PROTECTED]://projects.scipy.org/mailman/listinfo/numpy-discussion >> > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > There are several subroutines in LAPACK for this task.
http://www.netlib.org/lapack/double/dsyevx.f http://www.netlib.org/lapack/double/dsygvx.f IIRC symeig provides a wrapper. See http://mdp-toolkit.sourceforge.net/symeig.html Nils _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
