[SciPy-User] scipy.sparse.linalg.lobpcg broken?

Nico Schlömer nico.schloemer@gmail....
Wed Oct 13 09:50:49 CDT 2010


Really? I tried ones() instead, and got (with verbosity=10)

======================= *snip* =======================
Solving generalized eigenvalue problem with preconditioning

matrix size 10
block size 1

No constraints


iteration 0
[ True]
current block size: 1
eigenvalue: [ 100.]
residual norms: [ 990.]
iteration 1
[ True]
current block size: 1
eigenvalue: [ 0.]
residual norms: [  9.60596010e+12]
iteration 2
[ True]
current block size: 1
eigenvalue: [ 0.]
residual norms: [  1.63581388e+65]
iteration 3
Warning: invalid value encountered in multiply
[False]
Warning: invalid value encountered in multiply
final eigenvalue: [ 0.]
final residual norms: [ nan]
======================= *snap* =======================

We're still talking about the identity matrix, so I don't expect this
breakdown to be inherent in the method.

Cheers,
Nico



On Wed, Oct 13, 2010 at 4:29 PM,  <josef.pktd@gmail.com> wrote:
> On Wed, Oct 13, 2010 at 10:21 AM, Nico Schlömer
> <nico.schloemer@gmail.com> wrote:
>> Hi,
>>
>> I thought I give lobpcg a shot, and tried
>>
>> ====================== *snip* ======================
>> from scipy.sparse.linalg import lobpcg
>> from scipy.sparse import identity
>> import numpy as np
>>
>> n = 10
>> X = np.zeros( (n,1) )
>> A = identity( n )
>> lobpcg( A, X )
>> ====================== *snap* ======================
>>
>> On my machine, this yields
>>
>> ====================== *snip* ======================
>> Traceback (most recent call last):
>>  File "logpcg_test.py", line 8, in <module>
>>    lobpcg( A, X )
>>  File "/usr/lib64/python2.6/site-packages/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py",
>> line 304, in lobpcg
>>    blockVectorX, blockVectorBX = b_orthonormalize( B, blockVectorX )
>>  File "/usr/lib64/python2.6/site-packages/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py",
>> line 130, in b_orthonormalize
>>    gramVBV = sla.cholesky( gramVBV )
>>  File "/usr/lib64/python2.6/site-packages/scipy/linalg/decomp_cholesky.py",
>> line 66, in cholesky
>>    c, lower = _cholesky(a, lower=lower, overwrite_a=overwrite_a, clean=True)
>>  File "/usr/lib64/python2.6/site-packages/scipy/linalg/decomp_cholesky.py",
>> line 24, in _cholesky
>>    raise LinAlgError("%d-th leading minor not positive definite" % info)
>> numpy.linalg.linalg.LinAlgError: 1-th leading minor not positive definite
>> ====================== *snap* ======================
>>
>> Fail!
>>
>> Am I missing a library, or is that routine broken?
>
> It looks like a bug if X is all zeros. If at least 1 element of X is
> non-zero, it seems to work.
>
> Josef
>
>>
>> Cheers,
>> Nico
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>>
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