Bill Baxter wrote:
>  Just a guess, but I think the problem is just that usually when people
>  solve sparse equations the matrix is sparse, but the RHS vector is
>  dense.   I don't know if UMFPACK or SuperLU can actually handle a
>  sparse RHS vector, but if they can, then it sounds like a SciPy bug.
> 
>  I guess it should work if you convert your 'f' to a dense array before
>  making the calls to the solver.
> 
>  Regards,
>  --bb
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>    
With UMFPACK 4.4 and a dense RHS I get

    x = spsolve(K_dyn, f)
  File "/usr/lib64/python2.4/site-packages/scipy/linsolve/linsolve.py",
line 65, in spsolve
    return umf.linsolve( umfpack.UMFPACK_A, mat, b, autoTranspose = True )
  File
"/usr/lib64/python2.4/site-packages/scipy/linsolve/umfpack/umfpack.py",
line 566, in linsolve
    sol = self.solve( sys, mtx, rhs, autoTranspose )
  File
"/usr/lib64/python2.4/site-packages/scipy/linsolve/umfpack/umfpack.py",
line 508, in solve
    self._numeric, self.control, self.info )
  File
"/usr/lib64/python2.4/site-packages/scipy/linsolve/umfpack/_umfpack.py",
line 214, in umfpack_di_solve
    return __umfpack.umfpack_di_solve(*args)
ValueError: object too deep for desired array
> >> K_dyn
<71987x71987 sparse matrix of type '<type 'numpy.float64'> '
        with 3083884 stored elements (space for 3083884)
        in Compressed Sparse Column format> 

Any idea ?

Nils

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