On Tue, Feb 19, 2013 at 10:00 AM, Tony Ladd <tl...@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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