On Sun, Jan 15, 2012 at 6:54 AM, David Cournapeau <courn...@gmail.com>wrote:
> On Sat, Jan 14, 2012 at 11:53 PM, Nathan Faggian > <nathan.fagg...@gmail.com> wrote: > > Hi, > > > > I am finding it less than useful to have the negative index wrapping on > nd-arrays. Here is a short example: > > > > import numpy as np > > a = np.zeros((3, 3)) > > a[:,2] = 1000 > > print a[0,-1] > > print a[0,-1] > > print a[-1,-1] > > > > In all cases 1000 is printed out. > > > > What I am after is a way to say "please don't wrap around" and have > negative indices behave in a way I choose. I know this is a standard thing > - but is there a way to override that behaviour that doesn't involve cython > or rolling my own resampler? > > Although it could be possible with lots of work, it would most likely > be a bad idea. You will need to wrap something around your > model/data/etc... Could you explain a bit more what you have in mind ? > > David > Another approach that might be useful, depending on the needs, is to use `np.ravel_multi_index()`, in which ndim coords can be passed in and flatten coords are returned. It has options of 'raise', 'wrap' and 'clip' for handling out-of-bounds indices. It wouldn't be built directly into the arrays, but if that isn't needed, this might work. Ben Root
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