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SpikeInterface is a Python framework designed to unify preexisting spike sorting technologies into a single code base.
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With SpikeInterface, users can:
- read/write many extracellular file formats.
- pre-process extracellular recordings.
- run many popular, semi-automatic spike sorters (also in Docker/Singularity containers).
- post-process sorted datasets.
- compare and benchmark spike sorting outputs.
- compute quality metrics to validate and curate spike sorting outputs.
- visualize recordings and spike sorting outputs in several ways (matplotlib, sortingview, in jupyter)
- export report and export to phy
- offer a powerful Qt-based viewer in separate package spikeinterface-gui
- have some powerful sorting components to build your own sorter.
Detailed documentation for spikeinterface can be found here.
Several tutorials to get started can be found in spiketutorials.
There are also some useful notebooks on our blog that cover advanced benchmarking and sorting components.
You can also have a look at the spikeinterface-gui.
You can install the new spikeinterface version with pip:
pip install spikeinterface[full]The [full] option installs all the extra dependencies for all the different sub-modules.
To install all interactive widget backends, you can use:
pip install spikeinterface[full,widgets]To get the latest updates, you can install spikeinterface from sources:
git clone https://github.com/SpikeInterface/spikeinterface.git
cd spikeinterface
pip install -e .
cd ..If you find SpikeInterface useful in your research, please cite:
@article{buccino2020spikeinterface,
title={SpikeInterface, a unified framework for spike sorting},
author={Buccino, Alessio Paolo and Hurwitz, Cole Lincoln and Garcia, Samuel and Magland, Jeremy and Siegle, Joshua H and Hurwitz, Roger and Hennig, Matthias H},
journal={Elife},
volume={9},
pages={e61834},
year={2020},
publisher={eLife Sciences Publications Limited}
}