[Users] Announcing a new Python package for post-processing simulation data: kuibit

[Zach Etienne]

Excellent work Gabriele! I am excited to try out the new package. I agree
with Erik -- would be nice to see a demonstration of this in action!

-Zach

*     *     *
Prof. Zachariah Etienne
Physics & Astronomy Dept.
West Virginia University
http://astro.phys.wvu.edu/zetienne/
http://blackholesathome.net
<https://blackholesathome.net>


On Thu, Jan 14, 2021 at 8:25 AM Erik Schnetter <schnetter at cct.lsu.edu>
wrote:

> Gabriele
>
> This package looks quite interesting. Would you be interested in
> giving a show-and-tell presentation at some point, demonstrating how
> you use the package? I would be interested in attending.
>
> -erik
>
> On Thu, Jan 14, 2021 at 12:18 AM Gabriele Bozzola
> <bozzola.gabriele at gmail.com> wrote:
> >
> > Hello,
> >
> > I developed a new package to analyze Einstein Toolkit simulations,
> kuibit [0,1].
> > kuibit is a Python3.6+ code that I built from scratch following the same
> design
> > (and in various instances, implementation details too) of Wolfgang
> Kastaun's
> > PostCactus.
> >
> > kuibit provides high-level data types to easily work with grid
> functions, time
> > and frequency series, gravitational waves, and so on. It also has
> readers to
> > effortlessly access simulation data with full support for HDF5 and ASCII
> output
> > (1D, 2D, 3D grid data, scalar data, reductions, horizon data, ...). You
> can find
> > a reasonably comprehensive list of features in the documentation [2] or a
> > high-level summary in the frontpage of the docs [3].
> >
> > One of the main reasons I wrote this code is for other people to use it.
> > Our group (University of Arizona) is a young one and we don't have any
> sophisticated
> > toolchain to analyze simulation data. Without suitable tools,
> post-processing
> > simulations can be a daunting task for those that are new to the
> Einstein Toolkit.
> >
> > Given that I want other people to use kuibit, I made the effort to make
> the code user
> > and developer-friendly. For users, there is documentation [4] with
> examples and
> > small tutorials. Also, the package is on PyPI so it can be easily
> installed and updated.
> > For developers, the entire codebase has unit tests and continuous
> integration [5],
> > there are extensive comments, and the style of the code is rather verbose
> > to help developers understand what is going on. The continuous
> integration also
> > lints the code, performs static analysis, and generates the
> documentation,
> > reducing the maintenance costs.
> >
> > kuibit takes care of all the low-level details need to deal with
> simulation data, so
> > it greatly lowers the entry barrier in using the Einstein Toolkit. I
> believe that this,
> > along with the care I put in making the code accessible to other
> developers,
> > makes kuibit a good candidate for inclusion in the Einstein Toolkit.
> >
> > The main problem with kuibit is that it is a new code: regardless of all
> the
> > tests I wrote, there will be bugs, unergonomic interfaces, and
> performance issues.
> > kuibit needs to be tested with several real-world projects and
> cross-checked with
> > other codes.
> >
> > I am happy to give a short introduction to kuibit during a weekly call
> if there's
> > interest. In the meantime, the code is available here:
> > https://github.com/Sbozzolo/kuibit
> >
> > Best regards,
> > Gabriele Bozzola
> >
> > [0] https://github.com/Sbozzolo/kuibit
> > [1] https://github.com/Sbozzolo/kuibit#what-is-a-kuibit
> > [2] https://sbozzolo.github.io/kuibit/features.html
> > [3] https://sbozzolo.github.io/kuibit/#summary-of-features
> > [4] https://sbozzolo.github.io/kuibit/
> > [5] https://github.com/Sbozzolo/kuibit/actions
> > _______________________________________________
> > Users mailing list
> > Users at einsteintoolkit.org
> > http://lists.einsteintoolkit.org/mailman/listinfo/users
>
>
>
> --
> Erik Schnetter <schnetter at cct.lsu.edu>
> http://www.perimeterinstitute.ca/personal/eschnetter/
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