I played around with a C translation of that test program, and found that dgesvd (but not dgesdd) happens to converge and return all non-negative singular values for both operators I was having trouble with. I'm also looking at the Octave code just now, and I think they're using dgesvd also. Any one know why numpy uses dgesdd? speed?
On Tue, Feb 3, 2009 at 12:46 AM, Pauli Virtanen email@example.com wrote:
Mon, 02 Feb 2009 18:27:05 -0600, Robert Kern wrote:
On Mon, Feb 2, 2009 at 18:21, firstname.lastname@example.org wrote:
Hello list.. I've run into two SVD errors over the last few days. Both errors are identical in numpy/scipy.
I've submitted a ticket for the 1st problem (numpy ticket #990). Summary is: some builds of the lapack_lite module linking against system LAPACK (not the bundled dlapack_lite.o, etc) give a "LinAlgError: SVD did not converge" exception on my matrix. This error does occur using Mac's Accelerate framework LAPACK, and a coworker's Ubuntu LAPACK version. It does not seem to happen using ATLAS LAPACK (nor using Octave/Matlab on said Ubuntu)
These are almost certainly issues with the particular implementations of LAPACK that you are using. I don't think there is anything we can do from numpy or scipy to change this.
Yes, this is almost certainly a LAPACK problem. If in doubt, you can test it with the following F90 program (be sure to link it against the same LAPACK as Numpy). Save the matrices with 'np.savetxt("foo.txt", x.ravel ())' and run './test < foo.txt'.
program test implicit none integer, parameter :: N = 128 double precision :: A(N*N), S(N), U(N,N), Vh(N,N) double precision, allocatable :: WORK(:) double precision :: tmp integer :: IWORK(8*N) integer :: INFO = 0, LWORK
read(*,*) A A = reshape(transpose(reshape(A, (/N, N/))), (/ N*N /)) call dgesdd('A', N, N, A, N, S, U, N, Vh, N, tmp, -1, IWORK, INFO) LWORK = tmp if (info .ne. 0) stop 'lwork query failed' write(*,*) 'lwork:', lwork allocate(WORK(LWORK)) call dgesdd('A', N, N, A, N, S, U, N, Vh, N, WORK, LWORK, IWORK, INFO) write(*,*) 'info:', INFO write(*,*) 'min(S):', minval(S) if (INFO .ne. 0) then write(*,*) ' -> SVD failed to converge' end if if (minval(S) .lt. 0) then write(*,*) ' -> negative singular value' end if end program
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