Thank you for the suggestion, but it looks like that has the same behavior too:
In [43]: x = zeros(5) In [44]: idx = array([1,1,1,3,4]) In [45]: put(x,idx, [2,4,8,10,30]) In [46]: x Out[46]: array([ 0., 8., 0., 10., 30.]) On Wed, Jun 6, 2012 at 6:07 AM, Frédéric Bastien <[email protected]> wrote: > Hi, > > I get across the numpy.put[1] function. I'm not sure, but maybe it do > what you want. My memory are fuzy about this and they don't tell about > this in the doc of this function. > > Fred > > > [1] http://docs.scipy.org/doc/numpy/reference/generated/numpy.put.html > > On Wed, Jun 6, 2012 at 4:48 AM, John Salvatier > <[email protected]> wrote: > > Hello, > > > > I've noticed that If you try to increment elements of an array with > advanced > > indexing, repeated indexes don't get repeatedly incremented. For example: > > > > In [30]: x = zeros(5) > > > > In [31]: idx = array([1,1,1,3,4]) > > > > In [32]: x[idx] += [2,4,8,10,30] > > > > In [33]: x > > Out[33]: array([ 0., 8., 0., 10., 30.]) > > > > I would intuitively expect the output to be array([0,14, 0,10,30]) since > > index 1 is incremented by 2+4+8=14, but instead it seems to only > increment > > by 8. What is numpy actually doing here? > > > > The authors of Theano noticed this behavior a while ago so they python > loop > > through the values in idx (this kind of calculation is necessary for > > calculating gradients), but this is a bit slow for my purposes, so I'd > like > > to figure out how to get the behavior I expected, but faster. > > > > I'm also not sure how to navigate the numpy codebase, where would I look > for > > the code responsible for this behavior? > > > > _______________________________________________ > > NumPy-Discussion mailing list > > [email protected] > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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