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.