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