Nils Wagner wrote:
>  Aric Hagberg wrote:
>    
> > On Mon, Nov 20, 2006 at 09:45:47AM +0100, Nils Wagner wrote:
> >   
> >     
> >> Hi Neilen,
> >>
> >> In order to compare the results with the workhorse eig I have used a
> >> very small
> >> order n. The number of desired eigenpairs is equal to k=4 in my example,
> >> but the
> >> shape of the array of eigenvectors is (n,k+1) and for the eigenvalues it
> >> is (k+1,).
> >> The eigenvectors returned by arpack.eigen are zero.
> >>
> >> Nils
> >>     
> >>       
> > Hi Nils,
> >
> > The size of the return arrays are intentional (k+1).  This is 
> > the way ARPACK returns eigenvalues and eigenvectors for nonsymmetric
> > matrices.  I think the idea is that the k'th eigenvalue
> > (largest, smallest, etc) might be a complex conjugate pair and
> > then you might want k+1 (the conjugate).  Else, if the k'th
> > eigenvalue is real that entry is zero.   
> >
> > I can run your test example successfully.  Do the tests in
> > arpack/tests/test_arpack.py work for you?  
> >
> > Aric
> >
> >  
> >
> > _______________________________________________
> > Scipy-dev mailing list
> > Scipy-dev@[...].org
> > http://projects.scipy.org/mailman/listinfo/scipy-dev
> >   
> >     
>  help (arpack.eigen) yields
>  eigen(A, k=6, M=None, ncv=None, which='LM', maxiter=None, tol=0,
>  return_eigenvectors=True)
>      Return k eigenvalues and eigenvectors of the matrix A.
> 
>      Solves A * x[i] = w[i] * x[i], the standard eigenvalue problem for
>      w[i] eigenvalues with corresponding eigenvectors x[i].
> 
>      Inputs:
> 
>      A --  A matrix, array or an object with matvec(x) method to perform
>            the matrix vector product A * x.  The sparse matrix formats
>            in scipy.sparse are appropriate for A.
> 
>      k -- The number of eigenvalue/eigenvectors desired
> 
>      M -- (Not implemented)
>            A symmetric positive-definite matrix for the generalized
>            eigenvalue problem A * x = w * M * x
> 
>      Outputs:
> 
>      w -- An array of k eigenvalues
> 
>      v -- An array of k eigenvectors, k[i] is the eigenvector corresponding
>           to the eigenvector w[i]
> 
>  This info doesn't match with your explanation.
> 
>  Concerning the tests I get
> 
>  /usr/bin/python
>  /usr/lib64/python2.4/site-packages/scipy/sandbox/arpack/tests/test_speigs.py
>    Found 1 tests for __main__
> 
>   _naupd: Number of update iterations taken
>   -----------------------------------------
>      1 -    1:    17
> 
> 
>   _naupd: Number of wanted "converged" Ritz values
>   ------------------------------------------------
>      1 -    1:     4
> 
> 
>   _naupd: Real part of the final Ritz values
>   ------------------------------------------
>      1 -    4:   1.033E+00   7.746E-01   5.164E-01   2.582E-01
> 
> 
>   _naupd: Imaginary part of the final Ritz values
>   -----------------------------------------------
>      1 -    4:   0.000E+00   0.000E+00   0.000E+00   0.000E+00
> 
> 
>   _naupd: Associated Ritz estimates
>   ---------------------------------
>      1 -    4:   4.508E-17   7.450E-22   7.087E-26   4.834E-29
> 
> 
> 
>       =============================================
>       = Nonsymmetric implicit Arnoldi update code =
>       = Version Number:  2.4                      =
>       = Version Date:    07/31/96                 =
>       =============================================
>       = Summary of timing statistics              =
>       =============================================
> 
> 
>       Total number update iterations             =    17
>       Total number of OP*x operations            =    59
>       Total number of B*x operations             =     0
>       Total number of reorthogonalization steps  =    58
>       Total number of iterative refinement steps =     0
>       Total number of restart steps              =     0
>       Total time in user OP*x operation          =     0.004000
>       Total time in user B*x operation           =     0.000000
>       Total time in Arnoldi update routine       =     0.008000
>       Total time in naup2 routine                =     0.008000
>       Total time in basic Arnoldi iteration loop =     0.004000
>       Total time in reorthogonalization phase    =     0.000000
>       Total time in (re)start vector generation  =     0.000000
>       Total time in Hessenberg eig. subproblem   =     0.000000
>       Total time in getting the shifts           =     0.000000
>       Total time in applying the shifts          =     0.000000
>       Total time in convergence testing          =     0.000000
>       Total time in computing final Ritz vectors =     0.000000
> 
>  .
>  ----------------------------------------------------------------------
>  Ran 1 test in 0.107s
> 
>  OK
> 
> 
>  /usr/bin/python
>  /usr/lib64/python2.4/site-packages/scipy/sandbox/arpack/tests/test_arpack.py
>    Found 5 tests for __main__
>  .....
>  ----------------------------------------------------------------------
>  Ran 5 tests in 0.039s
> 
>  OK
>   
>  Nils
> 
> 
>  _______________________________________________
>  Scipy-dev mailing list
>  Scipy-dev@[...].org
>  http://projects.scipy.org/mailman/listinfo/scipy-dev
>    
Hi Aric,

Please can you run the following
 
I get something like

 _naupd: Number of update iterations taken
 -----------------------------------------
    1 -    1:    61


 _naupd: Number of wanted "converged" Ritz values
 ------------------------------------------------
    1 -    1:     0


 _naupd: Real part of the final Ritz values
 ------------------------------------------

 _naupd: Imaginary part of the final Ritz values
 -----------------------------------------------

 _naupd: Associated Ritz estimates
 ---------------------------------


     =============================================
     = Nonsymmetric implicit Arnoldi update code =
     = Version Number:  2.4                      =
     = Version Date:    07/31/96                 =
     =============================================
     = Summary of timing statistics              =
     =============================================


     Total number update iterations             =    61
     Total number of OP*x operations            =   225
     Total number of B*x operations             =     0
     Total number of reorthogonalization steps  =   118
     Total number of iterative refinement steps =     0
     Total number of restart steps              =     0
     Total time in user OP*x operation          =     0.008002
     Total time in user B*x operation           =     0.000000
     Total time in Arnoldi update routine       =     0.020002
     Total time in naup2 routine                =     0.020002
     Total time in basic Arnoldi iteration loop =     0.008002
     Total time in reorthogonalization phase    =     0.000000
     Total time in (re)start vector generation  =     0.000000
     Total time in Hessenberg eig. subproblem   =     0.008000
     Total time in getting the shifts           =     0.000000
     Total time in applying the shifts          =     0.004000
     Total time in convergence testing          =     0.000000
     Total time in computing final Ritz vectors =     0.000000

Traceback (most recent call last):
  File "eigs1.py", line 11, in ?
    w1,v1 = arpack.speigs.eigvals(matvec,a.shape[0],nev=nev,ncv=ncv)
  File
"/usr/lib64/python2.4/site-packages/scipy/sandbox/arpack/speigs.py",
line 71, in eigvals
    if info != 0: raise "Hell" # Indicates some error during the
Arnouldi iterations
Hell