cnrun
A NeuroML-enabled, precise but slow neuronal network simulator
CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua.
Available in
| Overlay | Newest | Ebuilds | Last activity | |
|---|---|---|---|---|
| science gitweb ↗ | 2.1.0-r2 | 1 | 4 d | details › |
Versions & arches
Use flags of 2.1.0-r2
2 expansion flags (python targets, ABIs, cpu flags…)
- lua_single_target_lua5-1
- lua_single_target_lua5-3