https://github.com/brian-team/brian2modelfitting
Model fitting toolbox for the Brian 2 simulator
https://github.com/brian-team/brian2modelfitting
Last synced: about 1 month ago
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Model fitting toolbox for the Brian 2 simulator
- Host: GitHub
- URL: https://github.com/brian-team/brian2modelfitting
- Owner: brian-team
- License: other
- Created: 2014-02-10T18:21:48.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2023-10-17T13:31:21.000Z (over 1 year ago)
- Last Synced: 2025-04-18T20:45:33.889Z (about 2 months ago)
- Language: Python
- Homepage: https://brian2modelfitting.readthedocs.io
- Size: 2.15 MB
- Stars: 15
- Watchers: 7
- Forks: 6
- Open Issues: 13
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
brian2modelfitting
==================
Model fitting toolbox for Brian 2 simulator.
[](https://doi.org/10.5281/zenodo.4601961)
The package [`brian2modelfitting`](https://brian2modelfitting.readthedocs.io) allows the user to find the best fit of the unknown free parameters for recorded traces and spike trains. It also supports simulation-based inference, where instead of point-estimated parameter values, a full posterior distribution over the parameters is computed.
By default, the toolbox supports a range of global derivative-free optimization methods, that include popular methods for model fitting: differential evolution, particle swarm optimization and covariance matrix adaptation (provided by the [`Nevergrad`](https://facebookresearch.github.io/nevergrad/), a gradient-free optimization platform) as well as Bayesian optimization for black box functions (provided by [`scikit-optimize`](https://scikit-optimize.github.io/stable/), a sequential model-based optimization library). On the other hand, simulation-based inference is the process of finding parameters of a simulator from observations by taking a Bayesian approach via sequential neural posterior estimation, likelihood estimation or ration estimation (provided by the [`sbi`](https://www.mackelab.org/sbi/)), where neural densitiy estimator, a deep neural network allowing probabilistic association between the data and underlying parameter space, is trained. After the network is trained, the approximated posterior distribution is available.
Documentation
-------------
[](https://brian2modelfitting.readthedocs.io)
The full documentation is available at http://brian2modelfitting.readthedocs.org.
Testing status
--------------
[](https://github.com/brian-team/brian2modelfitting/actions)
[](https://coveralls.io/github/brian-team/brian2modelfitting?branch=master)
Installation
------------
Install `brian2modelfitting` from the Python package index via pip:
```
pip install brian2modelfitting
```
The basic install only supports the optimization methods provided by the `Nevergrad` library. To install additional
algorithms, support for simulation-based inference, and other features, you can install the optional dependencies:
| extra | description | install command |
|---------|---------------------------------------------------------------------------------------|-------------------------------------------|
| `sbi` | simulation-based inference with [`sbi`](https://www.mackelab.org/sbi/) | `pip install 'brian2modelfitting[sbi]'` |
| `skopt` | optimization with [`sckikit-optimize`](https://scikit-optimize.github.io/) | `pip install 'brian2modelfitting[skopt]'` |
| `algos` | additional algorithms for `Nevergrad` | `pip install 'brian2modelfitting[algos]'` |
| `efel` | `FeatureMetric` with [`eFEL`](https://efel.readthedocs.io) electrophysiology features | `pip install 'brian2modelfitting[efel]'` |
| `test` | framework to run the test suite | `pip install 'brian2modelfitting[test]'` |
| `docs` | framework to build the documentation | `pip install 'brian2modelfitting[docs]'` |
| `all` | all of the above dependencies | `pip install 'brian2modelfitting[all]'` |
```
License
-------
The model fitting toolbox is released under the terms of the CeCILL 2.1 license and is available [here](https://github.com/brian-team/brian2modelfitting/blob/master/LICENSE).
Use
---
Please report issues at the GitHub [issue tracker](https://github.com/brian-team/brian2modelfitting/issues) or at the [Brian 2 discussion forum](https://brian.discourse.group).