[SciPy-dev] fast sorting of most numpy array types
Charles R Harris
Thu May 7 12:49:08 CDT 2009
On Thu, May 7, 2009 at 8:32 AM, Andrew Schein <email@example.com>wrote:
> Hi developers -
> I have recently release highly optimized type-specific C routines for
> sorting arrays of numeric types:
> The code was motivated in part by noting that the numpy implementation of
> sort appears to be a template-ized (over comparison) quicksort... and radix
> sort is often the better choice. Actually, it has been a few months since I
> looked at the numpy source, so don't quote me. The usort routines use a
> variety of strategies depending on the size of the array: radix sort, quick
> sort, insertion sort.
> I think the code could easily be incorporated in to numpy... and if there
> is interest in accepting such a change, I might find time to do it myself.
Numpy has quicksort, mergesort, and heapsort and now and then someone on the
list suggests adding radix sort. No doubt radix is suitable for certain
types, char arrays seem a natural. But there are problems with byte order
for the different integer types and floats can become complicated. And
unlike quicksort radix sort isn't done inplace. So it isn't clear that a
radix sort is the way to go for sorting in general but it could be useful in
Do you have some time results?
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