Thanks to all for a very quick response. np.bincount does what I need. Tony On 02/19/2013 10:04 AM, Benjamin Root wrote:
On Tue, Feb 19, 2013 at 10:00 AM, Tony Ladd <tladd@che.ufl.edu <mailto:tladd@che.ufl.edu>> wrote:
I want to accumulate elements of a vector (x) to an array (f) based on an index list (ind).
For example:
x=[1,2,3,4,5,6] ind=[1,3,9,3,4,1] f=np.zeros(10)
What I want would be produced by the loop
for i=range(6): f[ind[i]]=f[ind[i]]+x[i]
The answer is f=array([ 0., 7., 0., 6., 5., 0., 0., 0., 0., 3.])
When I try to use implicit arguments
f[ind]=f[ind]+x
I get f=array([ 0., 6., 0., 4., 5., 0., 0., 0., 0., 3.])
So it takes the last value of x that is pointed to by ind and adds it to f, but its the wrong answer when there are repeats of the same entry in ind (e.g. 3 or 1)
I realize my code is incorrect, but is there a way to make numpy accumulate without using loops? I would have thought so but I cannot find anything in the documentation.
Would much appreciate any help - probably a really simple question.
Thanks
Tony
I believe you are looking for the equivalent of accumarray in Matlab?
Try this:
http://www.scipy.org/Cookbook/AccumarrayLike
It is a bit touchy about lists and 1-D numpy arrays, but it does the job. Also, I think somebody posted an optimized version for simple sums recently to this list.
Cheers! Ben Root
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-- Tony Ladd Chemical Engineering Department University of Florida Gainesville, Florida 32611-6005 USA Email: tladd-"(AT)"-che.ufl.edu Web http://ladd.che.ufl.edu Tel: (352)-392-6509 FAX: (352)-392-9514