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BrainPy: A flexible and extensible framework for brain modeling

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Why to use BrainPy

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

  • JIT compilation for functions and class objects.
  • Numerical solvers for ODEs, SDEs, and others.
  • Dynamics simulation tools for various brain objects, like neurons, synapses, networks, soma, dendrites, channels, and even more.
  • Dynamics analysis tools for differential equations, including phase plane analysis and bifurcation analysis, and linearization analysis.
  • Seamless integration with deep learning models, and has the speed benefit on JIT compilation.
  • And more ......

BrainPy is designed to effectively satisfy your basic requirements:

  • Easy to learn and use: BrainPy is only based on Python language and has little dependency requirements.
  • Flexible and transparent: BrainPy endows the users with the fully data/logic flow control. Users can code any logic they want with BrainPy.
  • Extensible: BrainPy allow users to extend new functionality just based on Python coding. For example, we extend the same code with the ability to do numerical analysis (whatever low- or high-dimensional system).
  • Efficient: All codes in BrainPy can be just-in-time compiled (based on JAX and Numba) to run on CPU, GPU or TPU devices, thus guaranteeing its running efficiency.

How to use BrainPy

Step 1: installation

BrainPy is based on Python (>=3.6), and the following packages are required to be installed to use BrainPy:

  • NumPy >= 1.15
  • Matplotlib >= 3.4

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+
> # or
> git clone
> cd BrainPy
> python install

Other dependencies: you want to get the full supports by BrainPy, please install the following packages:

Step 2: useful links

Step 3: inspirational examples

Here list several examples of BrainPy. More detailed examples and tutorials please see BrainModels or BrainPy-Examples.

Neuron models

See brainmodels.neurons to find more.

Synapse models

See brainmodels.synapses to find more.

Network models

Dynamics Learning

Low-dimension dynamics analysis

High-dimension dynamics analysis

  • [Fixed point finder]

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