science

Software for Scientists and Engineers

This project provides software for engineering and natural science. http://en.opensuse.org/Portal:Science If you like to help to maintain the repository, please contact the respective maintainer: http://en.opensuse.org/openSUSE:Science_team For electrical engineering see electronics project: https://build.opensuse.org/project/show/electronics https://download.opensuse.org/repositories/science/Factory/ openSUSE:Factory

The next openSUSE distribution

openSUSE Tumbleweed: The Bleeding Edge, Perfected. Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing. * Always Current: Get the newest kernel, IDEs, desktops, and applications automatically. * Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on. * Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job. If you demand the latest stable software, your choice is Tumbleweed. Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects Have a look at http://en.opensuse.org/Portal:Factory for more details. https://download.opensuse.org/tumbleweed/repo/oss/ YODA

A small set of data analysis classes for MC event generator validation analyses

YODA is a small set of data analysis (specifically histogramming) classes being developed by MCnet members as a lightweight common system for MC event generator validation analyses. A few key features of YODA are as follows: * Storage of all information needed for statistically correct run combination and reweighting up to second-order correlations (e.g. variances, std devs, etc.) not just in the number of entries in a bin, but also the correlations of that with the x and y fill values. * Separation of statistics and data handling from presentation. YODA is primarily a library for doing the data part correctly: while we love really high quality data presentation, that's a separate goal. * A sensible class hierarchy for histogramming, recognising that a histogram contains details of fill history beyond the pure visual height of a bin, and that just counting weights, or binning arbitrary types on an axis are valuable operations. * Flexible data format support, including a new text-based, compact, and human-readable YODA format. * Proper and convenience treatment of "details" like irregular bin widths, gaps in contiguous binning, and overflows/underflows/etc. (incuding how they impact normalisation and calculation of histo- wide stat quantities) * Carefully designed programming interfaces in C++ and Python. We are very welcoming of feedback and design evolution, too!