[Numpy-discussion] Newbie indexing question [fancy indexing in nD]

[Pau Gargallo]

you can do things like

a[ list( ind[...,i] for i in range(.shape[-1]) ) ]

if the indices could be accessed as ind[i] instead of ind[...,i]
(transposing the indices array)
then you could simply do:

a[ list(ind) ]


pau

On 4/7/06, Angus McMorland <a.mcmorland at auckland.ac.nz> wrote:
> Hi again.
>
> Thanks, everyone, for your quick replies.
>
> Travis Oliphant wrote:
> > amcmorl wrote:
> >
> >> Hi all,
> >>
> >> I'm having a bit of trouble getting my head around numpy's indexing
> >> capabilities. A quick summary of the problem is that I want to
> >> lookup/index in nD from a second array of rank n+1, such that the last
> >> (or first, I guess) dimension contains the lookup co-ordinates for the
> >> value to extract from the first array. Here's a 2D (3,3) example:
> >>
> >> In [12]:print ar
> >> [[ 0.15  0.75  0.2 ]
> >>  [ 0.82  0.5   0.77]
> >>  [ 0.21  0.91  0.59]]
> >>
> >> In [24]:print inds
> >> [[[1 1]
> >>   [1 1]
> >>   [2 1]]
> >>
> >>  [[2 2]
> >>   [0 0]
> >>   [1 0]]
> >>
> >>  [[1 1]
> >>   [0 0]
> >>   [2 1]]]
> >>
> >> then somehow return the array (barring me making any row/column errors):
> >> In [26]: c = ar.somefancyindexingroutinehere(inds)
> >
> > You can do this with "fancy-indexing".   Obviously it is going to take
> > some time for people to get used to this idea as none of the responses
> > yet suggest it.
> > But the following works.
> > c = ar[inds[...,0],inds[...,1]]
> >
> > gives the desired effect.
> >
> > Thus, your simple description c[x,y] = ar[inds[x,y,0],inds[x,y,1]] is a
> > text-book description of what fancy-indexing does.
>
> Great. Turns out I wasn't too far off then. I've written a quick
> function of my own that extends the fancy indexing to nD:
>
> def fancy_index_nd(ar, ind):
>     evList = ['ar[']
>     for i in range(len(ar.shape)):
>         evList = evList + [' ind[...,%d]' % i]
>         if i < len(ar.shape) - 1:
>             evList = evList + [","]
>     evList = evList + [' ]']
>     return eval(''.join(evList))
>
> 1) Am I missing a simpler way to extend the fancy-indexing to
> n-dimensions? If not...
>
> 2) this seems (conceptually) that it might be a little faster than the
> routines that have to calculate a flat index. Hopefully it could be of
> use to people. Any thoughts?
>
> Cheers,
>
> Angus
> --
> Angus McMorland
> email a.mcmorland at auckland.ac.nz
> mobile +64-21-155-4906
>
> PhD Student, Neurophysiology / Multiphoton & Confocal Imaging
> Physiology, University of Auckland
> phone +64-9-3737-599 x89707
>
> Armourer, Auckland University Fencing
> Secretary, Fencing North Inc.
>
>
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