[SciPy-Dev] GSoC: Integrate library UNU.RAN into scipy.stats

Mon Apr 5 10:42:18 EDT 2021

Hi,

regarding the licence of UNU.RAN: I have obtained the permission from the
authors of UNU.RAN to include their package into SciPy under BSD. The only
part that we cannot use is a uniform random number generator in
src/uniform/mrg31k3p.c (Combined multiple recursive generator by Pierre
L'Ecuyer and Renee Touzin.)

Christoph

On Sun, Apr 4, 2021 at 6:00 PM <scipy-dev-request at python.org> wrote:

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> Today's Topics:
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>    1. Re: GSoC: Integrate library UNU.RAN into scipy.stats
>       (Andrea Gavana)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 4 Apr 2021 17:54:22 +0200
> From: Andrea Gavana <andrea.gavana at gmail.com>
> To: SciPy Developers List <scipy-dev at python.org>
> Subject: Re: [SciPy-Dev] GSoC: Integrate library UNU.RAN into
>         scipy.stats
> Message-ID:
>         <
> CAEf70byEr9gP38aJfw4zGt9qHfmct+LVAn0WgLakK_EkBcEGsw at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Hanno,
>
> On Sun, 4 Apr 2021 at 17.52, Hanno Klemm <h.klemm at gmx.de> wrote:
>
> > Hi Christoph, Tirth,
> >
> > this sounds like an interesting project, however, when I look at the
> > documentation of UNU.RAN, it seems to be licensed under the GPL. I always
> > thought that GPL is incompatible with scipy?s license?
> >
>
> As far as I have understood, the developers of UNU.RAN have opted for a
> much more open license if the library gets embedded into SciPy. I think I
> saw a message in the mailing list about that, but I can?t find it at the
> moment.
>
> Andrea.
>
>
>
> > Kind regards,
> > Hanno
> >
> > On 2. Apr 2021, at 21:44, Christoph Baumgarten <
> > christoph.baumgarten at gmail.com> wrote:
> >
> > ?
> >
> > Hi Tirth,
> >
> > great to hear that you are interested in the project! My main goal would
> > be to add the "universal" rv generation methods to SciPy, e.g. PINV, TDR
> (UNU.RAN
> > User Manual (wu.ac.at)
> > <
> http://statmath.wu.ac.at/software/unuran/doc/unuran.html#Methods_005ffor_005fCONT
> >).
> > At the moment, we just have one such function in SciPy (Statistical
> > functions (scipy.stats) ? SciPy v1.6.2 Reference Guide
> > <
> https://docs.scipy.org/doc/scipy/reference/stats.html#random-variate-generation
> >)
> > and it is very basic (I implemented it a while ago). Such functionality
> is
> > very useful in many situations, see e.g. OverflowError when sampling from
> > some handmade stats distributions ? Issue #13051 ? scipy/scipy (
> github.com)
> > <https://github.com/scipy/scipy/issues/13051> So the API would rather be
> > name_of_sampling_method(pdf / cdf, parameters of the sampling methods).
> >
> > Whether one should add a keyword to distribution.rvs(...) that allows the
> > user to choose the sampling method might be a question for a follow-up
> > project. This would also be quite time-consuming since you need to verify
> > which method is appropriate for a given distribution. A simpler task
> could
> > be to check if the rvs methods of a specific distribution could be
> > overwritten with the corresponding method in UNU.RAN (UNU.RAN User Manual
> > (wu.ac.at)
> > <http://statmath.wu.ac.at/software/unuran/doc/unuran.html#Stddist>).
> > For example, geninvgauss in SciPy relies on a Python implementation of a
> > rejection method / RoU and the implementation in UNU.RAN (gig / gig2)
> might
> > be faster. Also distributions with slow ppf methods relying on special
> > functions would be natural candidates. But that would also be of lower
> > priority for me.
> >
> > I hope it helps. Feel free to reach out if you have more questions.
> >
> > Christoph
> >
> > On Fri, Apr 2, 2021 at 6:00 PM <scipy-dev-request at python.org> wrote:
> >
> >> Send SciPy-Dev mailing list submissions to
> >>         scipy-dev at python.org
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> >> than "Re: Contents of SciPy-Dev digest..."
> >>
> >>
> >> Today's Topics:
> >>
> >>    1. Multivariate non-central hypergeometric distributions
> >>       (Wallenius' and Fisher's) (???? ?????????)
> >>    2. GSoC: Integrate library UNU.RAN into scipy.stats (Tirth Patel)
> >>
> >>
> >> ----------------------------------------------------------------------
> >>
> >> Message: 1
> >> Date: Fri, 2 Apr 2021 00:05:10 +0200
> >> From: ???? ????????? <samogot at gmail.com>
> >> To: scipy-dev at python.org
> >> Subject: [SciPy-Dev] Multivariate non-central hypergeometric
> >>         distributions (Wallenius' and Fisher's)
> >> Message-ID:
> >>         <
> >> CAMJZOa0xemJR7WCjcMcEyGUKvqMqPF6YDtLxbb+r2e4d1k-HDA at mail.gmail.com>
> >> Content-Type: text/plain; charset="utf-8"
> >>
> >> Hi everyone.
> >>
> >> Univariate versions of non-central hypergeometric distributions based
> >> on Agner Fog's BiasedUrn C++ code were added recently (in
> >> https://github.com/scipy/scipy/pull/13330). C++ code added in that PR
> >> already contains the implementation of multivariate versions of the same
> >> distributions. As far as I understand, the only things needed for
> >> multivariate distributions to work are Python wrapper and probably some
> >> tests.
> >>
> >> Is anyone interested in adding them? If not, I might get to it myself
> >> later
> >> this month, but as I haven't made any scipy contributions yet and am not
> >> familiar with the codebase, I will need much more time to rump up than
> an
> >> experienced contributor :)
> >>
> >> --
> >> Regards,
> >> Ivan Naydonov
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> >>
> >> ------------------------------
> >>
> >> Message: 2
> >> Date: Fri, 2 Apr 2021 19:19:26 +0530
> >> From: Tirth Patel <tirthasheshpatel at gmail.com>
> >> To: scipy-dev <scipy-dev at python.org>
> >> Subject: [SciPy-Dev] GSoC: Integrate library UNU.RAN into scipy.stats
> >> Message-ID:
> >>         <CABpuv38XtcJWOT6kskF_Rv3T=_
> >> 0iSoNCVr7gtnupL0kGQixfWg at mail.gmail.com>
> >> Content-Type: text/plain; charset="UTF-8"
> >>
> >> Hi all,
> >>
> >> I would like to participate in GSoC this year and found this project
> >> very interesting!
> >>
> >> TL; DR: I have a few questions regarding the project:
> >>   - Is the user interface desired as a separate python submodule
> >> (inside `scipy.stats`) or does it serve as an extension of the `rvs`
> >> method?
> >>   - Should UNU.RAN C library be included as a submodule within SciPy
> >> (e.g. gh-12043) or be cloned from a separate GitHub submodule (e.g
> >> gh-13328)?
> >>
> >> About Me
> >> ********
> >> I am Tirth (@tirthasheshpatel on GitHub), a third-year computer
> >> science undergrad student. I am quite familiar with Cython and a lot
> >> of my college courses make use of C. I have a good knowledge of
> >> probability theory and statistics.
> >>
> >> Open Source work: I have participated in GSoC with the PyMC team last
> >> year. I am a contributor to SciPy since May 2020 and recently a
> >> maintainer.
> >>
> >> About Project
> >> *************
> >> I had a question about the project. Is the user interface desired as a
> >> separate python submodule inside `scipy.stats`? like:
> >>
> >>     import scipy.stats as stats
> >>
> >>     # sample a 1000 variates from a normal distribution
> >>     # with mean 0 and std 1.5. Let UNU.RAN choose the method
> >>     rvs = stats.random.normal(0., 1.5, size=1000, method='auto')
> >>
> >>     # sample 100 samples from the beta distribution using TDR method
> >>     beta_rvs = stats.random.beta(1, 2, size=100, method='tdr')
> >>
> >>     # the `rvs` methods remains unaffected.
> >>     norm_rvs = stats.norm.rvs(0, 1.5, size=1000)
> >>
> >> Or does it serve as an extension of the `rvs` method:
> >>
> >>     from scipy.stats import norm, beta
> >>
> >>     # something like this:
> >>     # method = None => same behaviour as previous versions
> >>     # method = 'auto' => use UNU.RAN and let it choose the method
> >>     rvs = norm.rvs(0, 1.5, size=1000, method='auto')
> >>
> >>     beta_rvs = beta.rvs(1, 2, size=100, method='tdr')
> >>
> >> Also, should UNU.RAN C library be included as a submodule within SciPy
> >> (e.g. gh-12043) or be cloned from a separate GitHub submodule (e.g
> >> gh-13328)?
> >>
> >>
> >> --
> >> Kind Regards,
> >> Tirth
> >>
> >>
> >> ------------------------------
> >>
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