Emanuelle,
perfect! thanks.
> (assuming "import numpy as np", which is considered as a better practice
> as "from numpy import *")
actually I normally just "import numpy" but I guess np is nicer to
type and read...
cheers,
Damien
___
NumPy-Discussion
Hello Damien,
broadcasting can solve your problem (see
http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html):
(A[np.newaxis,:]**B[:,np.newaxis]).sum(axis=0)
gives the result you want.
(assuming "import numpy as np", which is considered as a better practice
as "from numpy import *")
Ch
ugh... I goofed. The code snippet should have read
from numpy import *
A=array([[1,2],[2,3],[3,4]])
B=array([[2,2],[3,3]])
C=zeros(A.shape)
for i in xrange(len(A)):
C[i]=(A[i]**B).sum(0)
print C
On Wed, Nov 18, 2009 at 2:17 PM, Damien Moore wrote:
> The title of this e-mail is probably mislead
The title of this e-mail is probably misleading so let me just show some code:
from numpy import *
A=array([[1,2],[2,3],[3,4]])
B=array([[2,2],[3,3]])
C=zeros(A.shape)
for i in xrange(len(A)):
C[i]=sum(A[i]**B)
print C
What I want to do is eliminate the for loop and rely on numpy
internals, but
