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- To: eigen@xxxxxxxxxxxxxxxxxxx
- Subject: Re: [eigen] SVD Bug
- From: Benoit Jacob <jacob.benoit.1@xxxxxxxxx>
- Date: Thu, 23 Sep 2010 07:59:34 -0400
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OK so what happens is that this SVD implementation computes a compact U:
m_matU.block(0,0,m,n) = A;
m_matU = A.block(0,0,m,m);
it doesn't bother extending the remaining rows by orthonormalization.
That actually isn't a bad thing. So the decomposition itself is fine.
We need to:
- document that aspect of U when taking the SVD of a rectangular matrix
- fix the solve method.
2010/9/23 Benoit Jacob <jacob.benoit.1@xxxxxxxxx>:
> 2010/9/23 Hauke Heibel <hauke.heibel@xxxxxxxxxxxxxx>:
>> I tried to look into it but failed. I can only say that already the
>> matrix U is strange since its last row is zero and this should not be
>> the case.
> Yes, indeed, that's very interesting:
> -0.08936 0.971
> -0.5195 -0.1061
> 0.3311 -0.4731
> -0.8752 -0.2161 0
> -0.009971 0.9026 0
> 0.4837 -0.3723 0
> 1.105 0
> 0 0.5873
> 0 0
> 0.2205 -0.9754
> -0.9754 -0.2205
> This unit test is really very insufficient. It should at least have
> checked that U is unitary.
>> I know that Benoit is still working on rewriting the SVD but at least
>> the bad memory access should be fixed.