Fri 14 Mar 2014 02:51:53 AM UTC, comment #5:
This bug is confirmed, and it is a regression from 3.6.4 where the dimensions are correct. The problem is with some new code added to handle low-dimension matrices where eigs shifts over to using eig instead. I'm adding jwe, who wrote that code, to the CC list for this bug.
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Fri 07 Mar 2014 11:25:45 AM UTC, comment #3:
(OP here)
The fact that V is 8x10 is the error. Since K is symmetric, it is expected that it holds that K = VDV'. For this product to be possible, V should be 10x8.
In reply to the oneliner working. It does indeed work, but also yields a V of unexpected dimensions.
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Fri 07 Mar 2014 09:01:54 AM UTC, comment #2:
There should be an edit-function.
Of course I could reproduce, that V is 8x10, but I don't know, whether that is an error. However, the oneliner really worked.
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Fri 07 Mar 2014 08:57:03 AM UTC, comment #1:
I tried to reproduce the error, but I couldn't.
Furthermore,
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Thu 06 Mar 2014 07:23:41 PM UTC, original submission:
The following code returns an unexpected result:
On my system, it shows that `V` is 8x10. However, this means that the product `VDV'` cannot be computed. From the documentation of eigs one would expect `V` to be 10x8:
"With two return arguments, V is a N-by-K matrix whose columns are the K eigenvectors corresponding to the returned eigenvalues."
(note that here, K = 8 and N = 10)
Checking the product `V(:, 1:r)DV(:, 1:r)'` shows that this corresponds to `Z(1:r, 1:r)`, indicating that the first `r` columns of `V` are correct, but the last 2 rows are omitted (instead of the last 2 columns, as expected).
Comparison with the same code in MATLAB R2013a shows that there `V` is 10x8 as expected.
As a final note, the following also fails
whereas the using 7 and 10 as value for K both work. A work-around is therefore to use:
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