[SciPy-User] get best few of many: argsort( few= ) using std::partial_sort ?

[Anne Archibald]

Just to complicate the issue somewhat, it might be valuable to have
both k-largest and k-smallest; also, one should think about what
happens to NaNs and infinities. Further, it might be worth including a
fast median calculation (i.e. find the median element(s) without
completely sorting the array).

Anne

On 8 July 2010 13:30, Keith Goodman <kwgoodman at gmail.com> wrote:
> On Thu, Jul 8, 2010 at 10:17 AM, denis <denis-bz-gg at t-online.de> wrote:
>> Folks,
>>  to get the best few of a large number of objects,
>> e.g. vectors near a given one, or small distances in
>> spatial.distance.cdist or .pdist,
>> argsort( bigArray )[: a few ] is not so hot.  It would be nice if
>>    argsort( bigArray, few= )
>> did this -- faster, save mem too. Would anyone else find this useful ?
>>
>> I recently stumbled across partial_sort in stl; fwiw,
>> std:partial_sort( A, A + sqrt(N), A + N ) is ~ 10 times faster than
>> std:sort
>> on my old mac ppc, even for N 100.
>> Also fwiw, nth_element alone is ~ twice as slow as partial_sort --
>> odd.
>
> I think a lot of people would like a partial sort. It comes up on the
> list now and then. There's a ticket with a cython partial sort:
>
> http://projects.scipy.org/numpy/ticket/1213
>
> Here's the docstring:
>
> def select(a, k, inplace=False):
>    '''
>    Wirth's version of Hoare's quick select
>
>    Parameters
>    ----------
>    a : array_like
>    k : integer
>    inplace : boolean
>        The partial sort is done inplace if a is a
>        contiguous ndarray and inplace=True.
>        Default: False.
>
>    Returns
>    -------
>    out : ndarray
>        Partially sorted a such that out[k] is
>        the k largest element. Elements smaller than
>        out[k] are unsorted in out[:k]. Elements larger
>        than out[k] are unsorted in out[k:].
>
>    '''
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