Introduction¶
- The
brian2modelfitting
toolbox provides three optimization classes: - and a simulation-based inference class:
All classes expect a model and the data as an input and return either the best fit of each parameter with the corresponding error, or a posterior distribution over unknown parameters. The toolbox can optimize over multiple traces (e.g. input currents) at the same time. It also allows the possiblity of simultaneous fitting/inferencing by taking into account multiple output variables including spike trains.
In following documentation we assume that brian2modelfitting
has been
installed and imported as follows:
from brian2modelfitting import *
Installation¶
To install the toolbox alongside Brian 2 simulator, use pip
as follows:
pip install brian2modelfitting
Testing Model Fitting¶
Version on master branch gets automatically tested with Travis services.
To test the code yourself, you will need to have pytest
installed and run
the following command inside the brian2modelfitting
root directory:
pytest