# [Numpy-discussion] SVD problem - matrices are not aligned

Sat Oct 23 21:33:50 CDT 2010

```> On Sat, Oct 23, 2010 at 7:00 PM, Daniel Wagner <daniel.wagner.ml@googlemail.com> wrote:
> Hi,
>
> I'm a new subscriber of this list. I hope to directly start with a question is ok...
>
> My question or problem:
> I've a matrix A which is calculated from the data b. The shapes of these matrices are:
> >>>A.shape
> (954, 9)
> >>>b.shape
> (954,)
>
> I calculate the SVD of A:
> >>> U, w, V = numpy.linalg.svd(A, full_matrices="True")
> >>>U.shape
> (954, 954)
>
> You want full_matrices set false so that U has shape (954, 9).
>
thanks! I tried it before with "False" as a string but of course this couldn't work. omgh. (no error message?)
Now I'm using:
>>>U, w, V = numpy.linalg.svd(yz_matrix_by, full_matrices=False)

> >>>W.diag(w)
> >>>W.shape
> (9,9)
> >>>V.shape
> (9,9)
>
> If I'm doing the check of the SVD results using:
> >>>numpy.allclose(A, numpy.dot(U, numpy.dot(W, V)))
> I get this error:
>
> easier, allclose(A, dot(U*w, V) )
>
That's right!
>
> "ValueError: matrices are not aligned"
>
>
> Mismatched dimensions.
>
Yeah, this error is away. Now I get:
>>>print(numpy.allclose(U_by*w_by, V_by))
False

I have to think about it if this makes sense ... (for me and prob. my my data)

Thanks and Greetings,
Daniel
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