Cool. Just as a heads up, for my algorithm to work, I actually need the indices, which is why argsort() is so important to me. I use it to get both ap_sorted and ws_sorted variables. If your weighted-quantile algo is faster and doesn't require those indices, please by all means change my implementation. Thanks.
On Thu, Aug 3, 2017 at 11:10 AM, Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote: > Not that I know of. The algorithm is very simple, requiring a > relatively small addition to the current introselect algorithm used > for `np.partition`. My biggest hurdle is figuring out how the calling > machinery really works so that I can figure out which input type > permutations I need to generate, and how to get the right backend > running for a given function call. > > -Joe > > On Thu, Aug 3, 2017 at 1:00 PM, Chun-Wei Yuan <chunwei.y...@gmail.com> > wrote: > > Any way I can help expedite this? > > > > On Fri, Jul 21, 2017 at 4:42 PM, Chun-Wei Yuan <chunwei.y...@gmail.com> > > wrote: > >> > >> That would be great. I just used np.argsort because it was familiar to > >> me. Didn't know about the C code. > >> > >> On Fri, Jul 21, 2017 at 3:43 PM, Joseph Fox-Rabinovitz > >> <jfoxrabinov...@gmail.com> wrote: > >>> > >>> While #9211 is a good start, it is pretty inefficient in terms of the > >>> fact that it performs an O(nlogn) sort of the array. It is possible to > >>> reduce the time to O(n) by using a similar partitioning algorithm to > the one > >>> in the C code of percentile. I will look into it as soon as I can. > >>> > >>> -Joe > >>> > >>> On Fri, Jul 21, 2017 at 5:34 PM, Chun-Wei Yuan <chunwei.y...@gmail.com > > > >>> wrote: > >>>> > >>>> Just to provide some context, 9213 actually spawned off of this guy: > >>>> > >>>> https://github.com/numpy/numpy/pull/9211 > >>>> > >>>> which might address the weighted inputs issue Joe brought up. > >>>> > >>>> C > >>>> > >>>> On Fri, Jul 21, 2017 at 2:21 PM, Joseph Fox-Rabinovitz > >>>> <jfoxrabinov...@gmail.com> wrote: > >>>>> > >>>>> I think that there would be a very good reason to have a separate > >>>>> function if we were to introduce weights to the inputs, similarly to > the way > >>>>> that we have mean and average. This would have some (positive) > repercussions > >>>>> like making weighted histograms with the Freedman-Diaconis binwidth > >>>>> estimator a possibility. I have had this change on the back-burner > for a > >>>>> long time, mainly because I was too lazy to figure out how to > include it in > >>>>> the C code. However, I will take a closer look. > >>>>> > >>>>> Regards, > >>>>> > >>>>> -Joe > >>>>> > >>>>> > >>>>> > >>>>> On Fri, Jul 21, 2017 at 5:11 PM, Chun-Wei Yuan < > chunwei.y...@gmail.com> > >>>>> wrote: > >>>>>> > >>>>>> There's an ongoing effort to introduce quantile() into numpy. You'd > >>>>>> use it just like percentile(), but would input your q value in > probability > >>>>>> space (0.5 for 50%): > >>>>>> > >>>>>> https://github.com/numpy/numpy/pull/9213 > >>>>>> > >>>>>> Since there's a great deal of overlap between these two functions, > >>>>>> we'd like to solicit opinions on how to move forward on this. > >>>>>> > >>>>>> The current thinking is to tolerate the redundancy and keep both, > >>>>>> using one as the engine for the other. I'm partial to having > quantile > >>>>>> because 1.) I prefer probability space, and 2.) I have a PR waiting > on > >>>>>> quantile(). > >>>>>> > >>>>>> Best, > >>>>>> > >>>>>> C > >>>>>> > >>>>>> _______________________________________________ > >>>>>> NumPy-Discussion mailing list > >>>>>> NumPy-Discussion@python.org > >>>>>> https://mail.python.org/mailman/listinfo/numpy-discussion > >>>>>> > >>>>> > >>>>> > >>>>> _______________________________________________ > >>>>> NumPy-Discussion mailing list > >>>>> NumPy-Discussion@python.org > >>>>> https://mail.python.org/mailman/listinfo/numpy-discussion > >>>>> > >>>> > >>>> > >>>> _______________________________________________ > >>>> NumPy-Discussion mailing list > >>>> NumPy-Discussion@python.org > >>>> https://mail.python.org/mailman/listinfo/numpy-discussion > >>>> > >>> > >>> > >>> _______________________________________________ > >>> NumPy-Discussion mailing list > >>> NumPy-Discussion@python.org > >>> https://mail.python.org/mailman/listinfo/numpy-discussion > >>> > >> > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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