On Jul 29, 2017 12:23, "Stephan Hoyer" <sho...@gmail.com> wrote:
This is an interesting idea, but I don't understand the use cases for this function. In particular, what would you use n-th order ratios for? There is no good use case for the nth order differences that I am aware of. I just added that to mimic the way diff works. One use case I can think of is estimating the slope of a log-scaled plot. But here exp(diff(log(x))) is an easy substitute. My original motivation was very similar to that. I was looking for the largest geometric gap in a sorted sequence of numbers. Taking logs and exponents seemed like a sledge hammer for that task. I guess ratio() would work in cases where values are both positive and negative, but again I don't know when that would be useful. If your signal crosses zero, ratios are likely to diverge. They would, but looking for sign changes is easy, and I added an argument to flag actual zeros. On Fri, Jul 28, 2017 at 3:25 PM Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote: > I have created PR#9481 to introduce a `ratio` function that behaves very > similarly to `diff`, except that it divides successive elements instead of > subtracting them. It has some handling built in for zero division, as well > as the ability to select between `/` and `//` operators. > > There is currently no masked version. Perhaps someone could suggest a > simple mechanism for hooking np.ma.true_divide and np.ma.floor_divide in as > the operators instead of the regular np.* versions. > > Please let me know your thoughts. > > Regards, > > -Joe > _______________________________________________ > 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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