>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. 
Hmm, I'm not sure I understand what is being done there.


On 15 July 2010 12:45, John Salvatier <jsalvati@u.washington.edu> 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 <bengioe@gmail.com> 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?

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         Emmanuel

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