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 <[email protected]> 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 > [email protected] > http://lists.einsteintoolkit.org/mailman/listinfo/users -- Erik Schnetter <[email protected]> http://www.perimeterinstitute.ca/personal/eschnetter/ _______________________________________________ Users mailing list [email protected] http://lists.einsteintoolkit.org/mailman/listinfo/users
