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 <jsalvati@u.washington.edu> 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?
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