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BrainPy
is an integrative framework for computational neuroscience and brain-inspired computation based on Just-In-Time (JIT) compilation (built on the top of JAX and Numba). Core functions provided in BrainPy includes
BrainPy
is designed to effectively satisfy your basic requirements:
BrainPy
is based on Python (>=3.6), and the following packages are required to be installed to use BrainPy
:
The installation details please see documentation: Quickstart/Installation
Method 1: install BrainPy
by using pip
:
To install the stable release of BrainPy, please use
> pip install -U brain-py
Method 2: install BrainPy
from source:
> pip install git+https://github.com/PKU-NIP-Lab/BrainPy
>
> # or
>
> git clone https://github.com/PKU-NIP-Lab/BrainPy
> cd BrainPy
> python setup.py install
Other dependencies: you want to get the full supports by BrainPy, please install the following packages:
JAX >= 0.2.10
, needed for "jax" backend and many other supports (how to install jax?)Numba >= 0.52
, needed for JIT compilation on "numpy" backend (how to install numba?)SymPy >= 1.4
, needed for dynamics "analysis" module and Exponential Euler method (how to install sympy?)Here list several examples of BrainPy. More detailed examples and tutorials please see BrainModels or BrainPy-Examples.
See brainmodels.neurons to find more.
See brainmodels.synapses to find more.
(Song, et al., 2016): Training excitatory-inhibitory recurrent network
[Working Memory] (Masse, et al., 2019): RNN with STP for Working Memory
A flexible and extensible framework for brain modeling
Python reStructuredText
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