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 > >
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