I get about 60% of the original execution times for about any size of stack.
On 15 July 2010 14:09, Charles R Harris wrote:
>
>
> On Thu, Jul 15, 2010 at 12:00 PM, Emmanuel Bengio wrote:
>
>> Ok I get it. Thanks!
>>
>> Numpy syntax that works for me:
>>
Ok I get it. Thanks!
Numpy syntax that works for me:
numpy.sum(a[:,:,:,numpy.newaxis]*b[:,numpy.newaxis,:,:],axis=-2)
On 15 July 2010 13:46, Charles R Harris wrote:
>
>
> On Thu, Jul 15, 2010 at 11:32 AM, Emmanuel Bengio wrote:
>
>> >Could you place all Rot's into
x27;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/n
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 fo
