10000 argsort does not work for multidimensional arrays · Issue #4724 · numpy/numpy · GitHub
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healther opened this issue May 19, 2014 · 12 comments
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argsort does not work for multidimensional arrays #4724

healther opened this issue May 19, 2014 · 12 comments

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@healther
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consider the following code:
a = np.random.random([5,5])
ind = np.argsort(a, axis=1)
a_sorted = a[ind]
np.sort(a, axis=1)

now a_sorted and a should be both sorted along the 1-axis. However not even the shapes are identical anymore. a is still of (5,5) while a_sorted is (5,5,5). If this is the intended behaviour, can someone tell me why?
@rkern
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rkern commented May 19, 2014

argsort() is working fine, but indexing doesn't work the way that you are expecting it to.

http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing

Try this:

a = np.random.random([5,5])
i = np.arange(len(a))[:, np.newaxis]
j = np.argsort(a, axis=1)
a_sorted = a[i, j]
np.sort(a, axis=1)

@pv pv closed this as completed May 19, 2014
@lzkelley
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I was confused in the same way. The documentation specifically states,

Returns
index_array : ndarray, int
Array of indices that sort a along the specified axis.
In other words, a[index_array] yields a sorted a.

Which only applies to a 1D array. Should the documentation be extended to specify that this is not the case for ND arrays?

@shoyer
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shoyer commented Oct 15, 2015

@lzkelley Yes, a patch to improve the documentation would be very welcome.

@lzkelley
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@shoyer cool, I'll make a PR for it and update

This was referenced Oct 19, 2015
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charris added a commit that referenced this issue Oct 23, 2015
@charris
Merge pull request #6548 from lzkelley/dev
5c286bc 
DOC: clarify usage of 'argparse' return value (see #4724).
jaimefrio pushed a commit to jaimefrio/numpy that referenced this issue Mar 22, 2016
@jaimefrio
DOC: clarify usage of 'argparse' return value.
d032a6f 
In response to Ticket numpy#4724, explain that the 'index_array' returned by
'argparse' can only be used to (directly) sort a one-dimensional input
array.
@endolith
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It would be good if there were an example of how to actually use the output to sort the N-D array.

It would also be good if there were a more readable solution than a[np.arange(np.shape(a)[0])[:,np.newaxis], np.argsort(a)]

@charris
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charris commented Dec 18, 2016

Maybe @seberg could make it one of his indexing function additions.

@seberg
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seberg commented Dec 18, 2016

I don't think it fits indexing very obviously, a pick function or so is probably an easier match.

@shoyer
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shoyer commented Dec 18, 2016

+1 for a new function.

@lzkelley
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Isn't the entire purpose of argsort (as apposed to sort) to be used for indexing?

@endolith
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argsort supplies the indexes to sort along an axis, but actually sorting along that axis using the indexes seems needlessly verbose. Unless there's a simpler way I'm not aware of.

@seberg
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seberg commented Dec 18, 2016

https://github.com/numpy/numpy/blob/5becd12914d0402967205579d6f59a98151e0d98/doc/neps/indexing.rst#related-questions

@eric-wieser
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a pick function or so is probably an easier match.

This is #8708

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9 participants
@pv @rkern @endolith @seberg @charris @eric-wieser @shoyer @lzkelley @healther
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