[Numpy-discussion] kind of a matrix multiplication

Olivier Delalleau shish@keba...
Tue Oct 11 07:59:46 CDT 2011


I don't really understand the operation you have in mind that should lead to
your desired result, so here's a way to get it that discards most of mat's
content: (which does not seem needed to compute what you want):

(stack.T * mat[0, 0]).T

-=- Olivier

2011/10/11 Martin Raspaud <martin.raspaud@smhi.se>

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> Hi all,
>
> I have a stack of vectors:
>
> v1 = np.arange(3)
> v2 = np.arange(3) + 3
> stack = np.vstack(v1, v2)
>
> (now stack is :
> array([[0, 1, 2],
>       [3, 4, 5]]))
>
> and a 3d matrix:
>
> mat = np.dstack((np.eye(3), np.eye(3) * 2))
> (mat is now
> array([[[ 1.,  2.],
>        [ 0.,  0.],
>        [ 0.,  0.]],
>
>       [[ 0.,  0.],
>        [ 1.,  2.],
>        [ 0.,  0.]],
>
>       [[ 0.,  0.],
>        [ 0.,  0.],
>        [ 1.,  2.]]]))
>
> I'm looking for the operation needed to get the two (stacked) vectors
> array([[0, 1, 2],
>       [6, 8, 10]]))
> or its transpose.
>
> I tried various combinations of tensor products, but I always get a
> result in 3 dimensions, while I just want two.
>
> Any suggestions ?
>
> Thanks,
> Martin
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