libdolfin2019.2gcc13
Shared libraries for DOLFIN
DOLFIN is the Python and C++ interface of the FEniCS project for the
automated solution of differential equations, providing a consistent
PSE (Problem Solving Environment) for solving ordinary and partial
differential equations. Key features include a simple, consistent and
intuitive object-oriented API; automatic and efficient evaluation of
variational forms; automatic and efficient assembly of linear
systems; and support for general families of finite elements.
elpa-erc
Powerful, modular, and extensible IRC client for Emacs
ERC is a powerful, modular, and extensible Internet Relay Chat (IRC)
client distributed with GNU Emacs since version 22.1.
librdkit1t64
Collection of cheminformatics and machine-learning software (shared libraries)
RDKit is a Python/C++ based cheminformatics and machine-learning software
environment. Features Include:
python3-dolfin
Base Python interface for DOLFIN (Python 3)
DOLFIN is the Python and C++ interface of the FEniCS project for the
automated solution of differential equations, providing a consistent
PSE (Problem Solving Environment) for solving ordinary and partial
differential equations. Key features include a simple, consistent and
intuitive object-oriented API; automatic and efficient evaluation of
variational forms; automatic and efficient assembly of linear
systems; and support for general families of finite elements.
visual-regexp
Interactively debug regular expressions
visual-regexp helps to design, debug or more generally work with the perl
regular expressions. Since it is often difficult to write the right regexp
on the first attempt, this tool will show the effect of regexp on a sample
that can be selected.
python3-pyspike
Python 3 library for the numerical analysis of spike train similarity
PySpike is a Python library for the numerical analysis of spike train
similarity. Its core functionality is the implementation of the
ISI-distance and SPIKE-distance as well as SPIKE-Synchronization. It
provides functions to compute multivariate profiles, distance
matrices, as well as averaging and general spike train processing.