[Numpy-discussion] stable sort for structured dtypes?
ben.root at ou.edu
Fri May 11 12:36:42 EDT 2012
On Fri, May 11, 2012 at 12:00 PM, Charles R Harris <
charlesr.harris at gmail.com> wrote:
> On Fri, May 11, 2012 at 9:01 AM, Benjamin Root <ben.root at ou.edu> wrote:
>> Hello all,
>> I need to sort a structured array in a stable manner. I am also sorting
>> only by one of the keys, so I don't think lexsort() is stable in that
>> respect. np.sort() allows for choosing 'mergesort', but it appears to not
>> be implemented for structured arrays. Am I going to have to create a new
>> plain array out of the one column I want to sort by, and run np.artsort()
>> with the mergesort in order to get around this? Or is there something more
>> straightforward that I am missing?
> Lexsort is just a sequence of indirect merge sorts, so using it to sort on
> a single column is the same as calling argsort(..., kind='mergesort').
> Mergesort (and heapsort) need to be extended to object arrays and arrays
> with specified comparison functions. I think that would be an interesting
> project for someone, I've been intending to do it myself but haven't got
> around to it.
> But as to your current problem, you probably need to have the keys in a
> plain old array. They also need to be in a contiguous array, but the sort
> methods take care of that by making contiguous copies when needed. Adding a
> step parameter to the sorts is another small project for someone. There is
> an interesting trade off there involving cache vs copy time vs memory usage.
Ok, that clears it up for me. I ended up just doing an
argsort(np.array(d['vtime']), kind=...) and use the indices as a guide. My
purpose didn't require a resorted array anyway, so this will do for now.
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