brian 2.5.4-4 source package in Ubuntu
Changelog
brian (2.5.4-4) unstable; urgency=medium
* gsl-compiler-arg.patch: remove: applied upstream.
* loongarch64.patch: new: further gsl optimizations.
Thanks to liuxiang (Closes: #1059428)
* d/rules: adjust hook for final cleanup.
This fixes latent lintian warnings in python-brian-doc after
architecture independent builds.
* pyproject-packages.patch: declare commit applied upstream.
-- Étienne Mollier <email address hidden> Fri, 29 Dec 2023 09:51:12 +0100
Upload details
- Uploaded by:
- Debian Med
- Uploaded to:
- Sid
- Original maintainer:
- Debian Med
- Architectures:
- any all
- Section:
- python
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| brian_2.5.4-4.dsc | 2.6 KiB | 430a5d3cd47399c4e5610b25131fdd1ca388937bcf14a616e920e6c25688d477 |
| brian_2.5.4.orig.tar.gz | 1.4 MiB | 50e89efd3480e1efc02f19e262eabfacd783c6accc3afbb071b3ca5162b89b21 |
| brian_2.5.4-4.debian.tar.xz | 20.0 KiB | 250a06f8fd42a7bd5e14b2aeb8caee95431b59be7ed39f496bf421a111af4689 |
Available diffs
- diff from 2.5.4-3 to 2.5.4-4 (2.2 KiB)
No changes file available.
Binary packages built by this source
- python-brian-doc: simulator for spiking neural networks - documentation
Brian is a clock-driven simulator for spiking neural networks. It is
designed with an emphasis on flexibility and extensibility, for rapid
development and refinement of neural models. Neuron models are
specified by sets of user-specified differential equations, threshold
conditions and reset conditions (given as strings). The focus is
primarily on networks of single compartment neuron models (e.g. leaky
integrate-and-fire or Hodgkin-Huxley type neurons).
.
This package provides user's manual (in HTML format), examples and
demos.
- python3-brian: simulator for spiking neural networks
Brian is a clock-driven simulator for spiking neural networks. It is
designed with an emphasis on flexibility and extensibility, for rapid
development and refinement of neural models. Neuron models are
specified by sets of user-specified differential equations, threshold
conditions and reset conditions (given as strings). The focus is
primarily on networks of single compartment neuron models (e.g. leaky
integrate-and-fire or Hodgkin-Huxley type neurons). Features include:
- a system for specifying quantities with physical dimensions
- exact numerical integration for linear differential equations
- Euler, Runge-Kutta and exponential Euler integration for nonlinear
differential equations
- synaptic connections with delays
- short-term and long-term plasticity (spike-timing dependent plasticity)
- a library of standard model components, including integrate-and-fire
equations, synapses and ionic currents
- a toolbox for automatically fitting spiking neuron models to
electrophysiological recordings
- python3-brian-lib: simulator for spiking neural networks -- extensions
Brian is a clock-driven simulator for spiking neural networks. It is
designed with an emphasis on flexibility and extensibility, for rapid
development and refinement of neural models. Neuron models are
specified by sets of user-specified differential equations, threshold
conditions and reset conditions (given as strings). The focus is
primarily on networks of single compartment neuron models (e.g. leaky
integrate-and-fire or Hodgkin-Huxley type neurons).
.
This package provides Python3 binary extensions.
- python3-brian-lib-dbgsym: debug symbols for python3-brian-lib
