Installation

BrainPy is designed to run on across-platforms, including Windows, GNU/Linux and OSX. It only relies on Python libraries.

Installation with pip

You can install BrainPy from the pypi. To do so, use:

pip install -U brainpy-simulator

Installation with Anaconda

You can install BrainPy from the anaconda cloud. To do so, use:

conda install brainpy-simulator -c brainpy

Installation from source

If you decide not to use conda or pip, you can install BrainPy from GitHub, or OpenI.

To do so, use:

pip install git+https://github.com/PKU-NIP-Lab/BrainPy

Or

pip install git+https://git.openi.org.cn/OpenI/BrainPy

To install the specific version of BrainPy, your can use

pip install -e git://github.com/PKU-NIP-Lab/BrainPy.git@V1.0.0

Package Dependency

The normal functions of BrainPy for dynamics simulation only relies on NumPy and Matplotlib. You can install these two packages through

pip install numpy matplotlib

# or

conda install numpy matplotlib

Some numerical solvers (such like exponential euler methods) and the dynamics analysis module heavily rely on symbolic mathematics library SymPy. Therefore, we highly recommend you to install sympy via

pip install sympy

# or

conda install sympy

If you use BrainPy for your computational neuroscience project, we recommend you to install Numba. This is because BrainPy heavily rely on Numba for speed acceleration in almost its every module, such like connectivity, simulation, analysis, and measurements. Numba is also a suitable framework for the computation of sparse synaptic connections commonly used in the computational neuroscience project. Install Numba is a piece of cake. You just need type the following commands in you terminal:

pip install numba

# or

conda install numba

As we stated later, BrainPy is a backend-independent neural simulator. You can define and run your models on nearly any computation backends you prefer. These packages can be installed by your project’s need.