SpikeToolkit
SpikeToolkit is a package of the SpikeInterface project is designed for efficient preprocessing, postprocessing, evaluation, and curation of extracellular datasets and spike sorting outputs.
Getting Started
To get started with SpikeToolkit, you can install it with pip:
pip install spiketoolkit
You can also get SpikeToolkit through the spikeinterface package:
pip install spikeinterface
You can also install SpikeToolkit locally by cloning the repo into your code base. If you install SpikeToolkit locally, you need to run the setup.py file.
git clone https://github.com/SpikeInterface/spiketoolkit.git
cd spiketoolkit
python setup.py install
Examples
For more information about how to use SpikeToolkit, please checkout these examples.
Documentation
All documentation for SpikeInterface can be found here: https://spikeinterface.readthedocs.io/en/latest/.
Authors
Alessio Paolo Buccino - Center for Inegrative Neurolasticity (CINPLA), Department of Biosciences, Physics, and Informatics, University of Oslo, Oslo, Norway
Cole Hurwitz - The Institute for Adaptive and Neural Computation (ANC), University of Edinburgh, Edinburgh, Scotland
Jeremy Magland - Center for Computational Biology (CCB), Flatiron Institute, New York, United States
Matthias Hennig - The Institute for Adaptive and Neural Computation (ANC), University of Edinburgh, Edinburgh, Scotland
Samuel Garcia - Centre de Recherche en Neuroscience de Lyon (CRNL), Lyon, France
Josh Siegle - Allen Institute for Brain Science, Seattle, United States
For any correspondence, contact Alessio Buccino at alessiop.buccino@gmail.com
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file spiketoolkit-0.5.1.tar.gz.
File metadata
- Download URL: spiketoolkit-0.5.1.tar.gz
- Upload date:
- Size: 43.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.1 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.6.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fc7c31f343ee4a3472418821b6de9ce706109a8e8c6f60c5ae095002acfc5a59
|
|
| MD5 |
083c56cc64727a013b0c345f63720179
|
|
| BLAKE2b-256 |
41bd60c7dacec622a650310d49d96f59766f4cdf5da0ecdfed62510109b5d573
|
