On Tue, Feb 16, 2016 at 1:41 PM, Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote:
> Thanks for pointing me to that. I had something a bit different in > mind but that definitely looks like a good start. > > On Tue, Feb 16, 2016 at 1:32 PM, Antony Lee <antony....@berkeley.edu> > wrote: > > See earlier discussion here: https://github.com/numpy/numpy/issues/6326 > > Basically, naïvely sorting may be faster than a not-so-optimized version > of > > quickselect. > > > > Antony > > > > 2016-02-15 21:49 GMT-08:00 Joseph Fox-Rabinovitz < > jfoxrabinov...@gmail.com>: > >> > >> I would like to add a `weights` keyword to `np.partition`, > >> `np.percentile` and `np.median`. My reason for doing so is to to allow > >> `np.histogram` to process automatic bin selection with weights. > >> Currently, weights are not supported for the automatic bin selection > >> and would be difficult to support in `auto` mode without having > >> `np.percentile` support a `weights` keyword. I suspect that there are > >> many other uses for such a feature. > >> > >> I have taken a preliminary look at the C implementation of the > >> partition functions that are the basis for `partition`, `median` and > >> `percentile`. I think that it would be possible to add versions (or > >> just extend the functionality of existing ones) that check the ratio > >> of the weights below the partition point to the total sum of the > >> weights instead of just counting elements. > >> > >> One of the main advantages of such an implementation is that it would > >> allow any real weights to be handled correctly, not just integers. > >> Complex weights would not be supported. > >> > >> The purpose of this email is to see if anybody objects, has ideas or > >> cares at all about this proposal before I spend a significant amount > >> of time working on it. For example, did I miss any functions in my > >> list? > >> > >> Regards, > >> > >> -Joe > >> _______________________________________________ > >> NumPy-Discussion mailing list > >> NumPy-Discussion@scipy.org > >> https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > statsmodels just got weighted quantiles https://github.com/statsmodels/statsmodels/pull/2707 I didn't try to figure out it's computational efficiency, and we would gladly delegate to whatever fast algorithm would be in numpy. Josef
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