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 <[email protected]> > -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA1 > > 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/ > > iQEcBAEBAgAGBQJOk9jWAAoJEBdvyODiyJI4y30IAJu6YIHK+ED8pN5M2TFrEKj8 > k/K22MjitlQ8wTFDxwc5xBRI+yoniqgAfpzWjdU3pc5MxzXRgbZrRZagYWjepZyI > CtN/CHy+BfM8EPJulFeVcInAgo1pgfAhH4xwEakbu88XhKSgat1Y9xlNRcrohTUQ > oBVd+DNmBYpEUAa0pDjkMYXM8vaJqzePZZGaviZxY0AY2MBDrbZN/z6t4u2Unajn > 8X1vjCg/XfDbm9v7FK/52MUorAJinZRdHiWBTE9rOmAqjJxTBoFKkN+0FMTUk6Sj > acJNjr5KFjl6o3JPxqU4jRfw1zFRO9BEouzosKfYcs/kLozNjTBmfZztg0np/dg= > =Ykij > -----END PGP SIGNATURE----- > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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