[Numpy-discussion] kind of a matrix multiplication

[Martin Raspaud]

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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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[Martin Raspaud]

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On 11/10/11 07:49, Martin Raspaud wrote:
> Hi all,
[...]

> I'm looking for the operation needed to get the two (stacked) vectors
> array([[0, 1, 2],
> [6, 8, 10]]))
> or its transpose.

Hi again,

Here is a solution I just found:
np.einsum("ik, jki->ij", stack, mat)
array([[ 0., 1., 2.],
[ 6., 8., 10.]])

Best regards,

Martin
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[Olivier Delalleau]

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....@smhi.se>

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