[SciPy-Dev] GSoC'17: Circular statistics

[josef.pktd at gmail.com]

On Wed, Mar 15, 2017 at 6:47 PM, Todd <toddrjen at gmail.com> wrote:
>
>
> On Mar 11, 2017 14:50, "Vladislav Iakovlev" <iavlaserg at gmail.com> wrote:
>
> Hello!
>
>
> My name is Vladislav Iakovlev. I am a master student of Department of
> Applied Math, HSE University, Moscow, Russia. I have never contributed to
> open source projects, but I would be happy to start it with SciPy.
>
>
> I noticed that existing functionality for circular statistics is
> insufficient. So, I want to suggest an idea for GSoC: implement it to
> scipy.stats. My plan is to do it through the next steps:
>
> 1)      Develop the class rv_circular, analogous to rv_continuous adjusted
> to circular statistic functions.
>
> 2)      Develop derived classes for circular distributions.
>
> 3)      Develop point estimations and statistical tests functions.
>
> During the summer, I assume to implement materials from chapters 1-8 of the
> book “MARDIA, K. V. AND JUPP , P. E. (2000), Directional Statistics, John
> Wiley”, documentation and unit tests for it.
>
>
> Is this idea interesting for the Community? I’m glad to any feedback.
>
>
> This may be a little crazy, but would it be possible to wait for
> parameterized dtypes and create a circular dtype to handle all this
> automagically?

A dtype will not know statistics. AFAIU, I would be just something
like a substitute for units as in astropy, somewhere there still needs
to be the code to compute statistics on a circle or sphere or ...

(Personally, I like plain float and complex ndarrays and prefer to
leave all units, datetimes and whatever in a wrapper for the interface
but out of the algorithms.)

One design decision for rv_circular is how to handle integration on a
circle, i.e. how to map cdf on R into a cdf on a circle, and the
associated integration over subintervals.
vonmised.cdf is defined on R which turned out to be computationally
convenient but doesn't make a "proper" cdf that is e.g. limited to [0,
1] and doesn't define support bounds for integration.

Josef


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