libadios2-serial-plugins

ADIOS2 Adaptable IO system for simulations - core libraries (serial)

The Adaptable IO System (ADIOS) provides a simple, flexible way for scientists to describe the data in their code that may need to be written, read, or processed outside of the running simulation. By providing an external to the code XML file describing the various elements, their types, and how you wish to process them this run, the routines in the host code (either Fortran or C) can transparently change how they process the data.

libnet-amazon-signature-v4-perl

module for the Amazon Web Services signature version 4

Net::Amazon::Signature::V4 signs an HTTP::Request to Amazon Web Services by appending an Authorization header. Amazon Web Services signature version 4, AWS4-HMAC-SHA256, is used.

libmodule-build-pluggable-cpanfile-perl

plugin for Module::Build::Pluggable to use cpanfiles

Module::Build::Pluggable::CPANfile is a plugin for Module::Build::Pluggable to include dependencies from cpanfile into meta files.

python3-litestar

Powerful, flexible, highly performant, opinionated ASGI framework

LiteStar is a Python web framework (similar to FastAPI and Django) that is designed to be simply but also very flexible. It is built with the goal of being easy to learn and use, making it an excellent choice for both beginners and experienced developers. LiteStar follows the WSGI (Web Server Gateway Interface) standard, which means it can run on various web servers and is compatible with popular Python web server gateways like Gunicorn and uWSGI.

r-cran-cvar

GNU R package to Computed Expected Shortfall and Value at Risk

Compute expected shortfall (ES) and Value at Risk (VaR) from a quantile function, distribution function, random number generator or probability density function. ES is also known as Conditional Value at Risk (CVaR). Virtually any continuous distribution can be specified. The functions are vectorized over the arguments. The computations are done directly from the definitions, see e.g. Acerbi and Tasche (2002) <doi:10.1111/1468-0300.00091>. Some support for GARCH models is provided, as well.

r-cran-sftime

GNU R support for simple feature objects that have a time column

Classes and methods for spatial objects that have a registered time column, in particular for irregular spatiotemporal data. The time column can be of any type, but needs to be ordinal. Regularly laid out spatiotemporal data (vector or raster data cubes) are handled by package 'stars'.