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 -----BEGIN PGP SIGNATURE----- Version: GnuPG v2.0.14 (GNU/Linux) Comment: Using GnuPG with Red Hat - http://enigmail.mozdev.org/

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