Hi again everyone! So far we have implemented *scipy.stats.directionalmean* ( https://github.com/scipy/scipy/pull/16435) which was straight forward. For circular data, the result agrees with circmean. Take a look at the Docs at: https://scipy.github.io/devdocs/reference/generated/scipy.stats.directionalm... API wise it was decided that Input data must be shaped as (...., n) where n denotes the dimensionality of the vector data. Then the statistic is computed over the last axis. By default, input data are also normalized to unit vectors. Implementing the directional variance/dispersion is a bit more tricky. Unfortunately, there does not seem to be a universal definition of it in the literature. The most common definition by Mardia and Jupp is 2(1-R) where R is the mean resultant length of the input vectors. This is twice as much as for the circular variance where the definition is unambiguous. There are two options: *not implementing* directional variance or to name the function directional*_dispersion*. We would love to hear your thoughts on this here or in https://github.com/scipy/scipy/pull/16785 . Best Am So., 5. Juni 2022 um 20:09 Uhr schrieb Pamphile Roy < roy.pamphile@gmail.com>:
Hi Daniel,
I also think these would be interesting.
I am myself very interested in the sampling part, as we actually recently added poisson disk sampling which internally uses hypersphere sampling. I would be happy to help with this work.
Cheers, Pamphile (@tupui)
On 5 Jun 2022, at 17:04, Robert Kern <robert.kern@gmail.com> wrote:
Yes, I think both have a place in scipy.stats. Thanks!
On Sun, Jun 5, 2022 at 5:55 AM Daniel Schmitz < danielschmitzsiegen@googlemail.com> wrote:
Hi everyone,
recently questions came up with regards to statistics on the unit sphere in scipy.
Issue 12041 <https://github.com/scipy/scipy/issues/12041> raises the question if spherical mean/variance should be added as descriptive statistics similar to circmean/circvar <https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.circvar.htm...> . The canonical reference for all things related to statistics on the unit sphere is "Directional Statistics" by Mardia & Jupp.
Another important basic functionality is the generation of random samples on the unit sphere: discussion was started in this issue <https://github.com/scipy/scipy/issues/16205> .
Any strong opinion against these? I think at least the random number generation is reimplemented every day around the world (done so myself at least 2 times) and would strongly benefit from being part of scipy.
Best _______________________________________________ SciPy-Dev mailing list -- scipy-dev@python.org To unsubscribe send an email to scipy-dev-leave@python.org https://mail.python.org/mailman3/lists/scipy-dev.python.org/ Member address: robert.kern@gmail.com
-- Robert Kern _______________________________________________ SciPy-Dev mailing list -- scipy-dev@python.org To unsubscribe send an email to scipy-dev-leave@python.org https://mail.python.org/mailman3/lists/scipy-dev.python.org/ Member address: roy.pamphile@gmail.com
_______________________________________________ SciPy-Dev mailing list -- scipy-dev@python.org To unsubscribe send an email to scipy-dev-leave@python.org https://mail.python.org/mailman3/lists/scipy-dev.python.org/ Member address: danielschmitzsiegen@googlemail.com