eigs(A[, B], ; nev=6, which=”LM”, tol=0.0, maxiter=1000, sigma=nothing, ritzvec=true, v0=zeros((0, ))) -> (d[, v ], nconv, niter, nmult, resid) eigs computes eigenvalues d of A using Lanczos or Arnoldi iterations for real symmetric or general nonsymmetric matrices
nev= number of eigens... Paul W dniu niedziela, 15 marca 2015 21:10:08 UTC+1 użytkownik Erik Schnetter napisał: > > I am looking for a routine that calculate the SVD (singular value > decomposition) of a square, complex, dense, non-symmetric matrix. I am > aware of Julia's SVD routine (and the respective LAPACK routines that one > could call directly). However, I don't need all of the singular values -- I > need only the largest one (or some of the largest ones), as well as the > associated entries of U. Is there such a routine? I didn't find one in > Julia. > > I've looked for other packages that could be wrapped, but couldn't find > any that offers this feature. The only thing I found is a description of > the "svds" Matlab routine, which is apparently based on "eigs". > > -erik > > -- > Erik Schnetter <[email protected] <javascript:>> > http://www.perimeterinstitute.ca/personal/eschnetter/ > > My email is as private as my paper mail. I therefore support encrypting > and signing email messages. Get my PGP key from https://sks-keyservers.net. > > >
