python3-sphinx-inline-tabs

Add inline tabbed content to your Sphinx documentation

This module has a small footprint in the markup and generated website, with an elegant design.

dict-freedict-nld-pol

Dutch-Polish dictionary for the dict server/client

This is the Dutch-Polish dictionary from the FreeDict project. It contains 11475 headwords (FreeDict status: big enough to be useful). It can be either used with the dictd server and a dict client or with GoldenDict.

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.

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'.

libstarpu-1.3-9

Task scheduler for heterogeneous multicore machines

StarPU is a runtime system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs or on Cell's SPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.