brian2
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Brian is a free, open source simulator for spiking neural networks.
We have a ``run_regularly`` method and ``network_operation``, but people often want to have something run just once and it's a bit of a fiddle at the moment. How about we...
Hi there! I just adapted the [test_synapses_to_synapses.py](https://github.com/brian-team/brian2/blob/b750fea045fc23bbf5e795ba6e7930dcc5be8747/brian2/tests/test_synapses.py#L2013-L2026) test to find out if I need to take care of some form of subgroups when the targat of a `SynapticPathway` is a...
The current Cython implementation for Cython (i.e. `rand()` and `randn()`) jumps through some hoops to call numpy's random functions via Python, buffering it in a numpy array. Since numpy 1.8,...
As reported in the [discourse forum](https://brian.discourse.group/t/weakly-referenced-in-object-neurongroup-stateupdater/215), using a `VariableView` of a subgroup in `linked_var` will lead to a `ReferenceError`. The following example reproduces the issue: ```Python group1 = NeuronGroup(10, 'v...
Having an ``Equations.prefix`` and/or ``Equations.postfix`` notation that returned a copy of the equations with all variables prefixed/postfixed with a given string could make it much easier and simpler to write...
Continuing the discussion from #1051 and the [Discourse forum](https://brian.discourse.group/t/standards-in-compartmental-modeling-libraries-of-mechanisms/148/7) here. No need to look at the actual code yet, it is just a quick&dirty dummy implementation to get things working....
In the context of automatic model descriptions, it would be useful to be able to give additional descriptions/annotations to objects such as `NeuronGroup`. Currently, the only type of annotation you...
e.g. define `E(vT)=exp((E-v+vT)/tau)` and then use `E(15*mV)`, `E(40*mV)` in the rest of the equations.
[This has already been mentioned in #251, but I'm pulling it out since it is quite simple to do and useful without full encapsulation support] Currently, you can give a...
Running multiple standalone simulations of the same model with different parameters is quite cumbersome at the moment. We can support this much more efficiently by using the trick I show...