>Could you place all Rot's into the same array and all the Trans's into the same array? Well I guess since they're all the same size. I would just have to do array(a). But the result of the dot product of two 3d arrays is most unexpected: >>> a = numpy.ones((4,5,6)) >>> a = numpy.ones((10,4,4)) >>> b = numpy.ones((10,4,4)) >>> c = numpy.dot(a,b) >>> c.shape (10, 4, 10, 4) #Hmm, not what a newbie expects D:
>Yes, there is a trick for this using a multiply with properly placed newaxis followed by a sum. It uses more memory but for stacks of small arrays that shouldn't matter. See the post here<http://thread.gmane.org/gmane.comp.python.numeric.general/20360/focus=21033>. Hmm, I'm not sure I understand what is being done there. On 15 July 2010 12:45, John Salvatier <[email protected]> wrote: > Could you place all Rot's into the same array and all the Trans's into the > same array? If you have the first index of each array refer to which array > it is numpy.dot should work fine, since numpy.dot just does the dot product > over the second to last and last indexes. > http://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html > > John > > On Thu, Jul 15, 2010 at 9:38 AM, Emmanuel Bengio <[email protected]>wrote: > >> Hello, >> >> I have a list of 4x4 transformation matrices, that I want to "dot with" >> another list of the same size (elementwise). >> Making a for loop that calculates the dot product of each is extremely >> slow, >> I thought that maybe it's due to the fact that I have thousands of >> matrices and it's a python for loop and there's a high Python overhead. >> >> I do something like this: >> >> for a,b in izip(Rot,Trans): >> >> c.append(numpy.dot(a,b)) >> >> Is there a way to do this in one instruction? >> Or is there a way to do this all using weave.inline? >> >> -- >> >> >> Emmanuel >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- Emmanuel
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